Fundamentals of ResearchMethodology Dr.S.Saravanan M.Com., M.Phil., MBA.,MBA., PGDCA., Ph.D Associate Professor Post Graduate and Research Department of Commerce with Computer Applications Dr.N.G.P Arts and Science College Coimbatore-641048 Tamilnadu. Vanmathi Publishers Kannan Nagar Tiruppur – 641 604. Tamil Nadu
[email protected] First edition 2011 Vanmathi Publishers Kannan Nagar, Tiruppur - 641604. Tamil Nadu This book or any part thereof may not be Reproduced in any form without the Written permission of the publisher ISBN : 978-81-920808-0-2 Preface The basic purpose of this book is to assist the readers to develop a scrupulous understanding of the various concepts in a systematic way. Although there are good number of standard books on “Research Methodology” there are difference in the adoption and approaches of the methods of applying the concepts and emphasis on lucidity. The whole book has been written very carefully and each chapter has been discussed in detail in order to meet the requirement of the students. I sincerely hope that the students, learned teachers, research scholars and other readers will find the book useful. However I shall be grateful if the mistakes and deficiencies are pointed out by the readers. Constructive criticisms and suggestions for improvement of the book are most welcome from researchers and students for further development of the subject content as well as the presentation of this book. I fall short of words to express thank my family members and dear ones, who have stood beside me while I immersed in writing this book, oblivious of their needs for my time and attention. I am extremely thankful to my students and learned colleagues in the college for providing the essential stimulus for writing this book. I am grateful to all those persons whose writings and works have helped me in the preparation of this book. I am indebted to the reviewer of this book whose invaluable inputs have made extremely enhancing the value of the content. My sincere gratitude is due to M/s Vanmathi publishers for their tireless endeavor in bringing out this book well in time. Last I record my gratitude to god almighty for giving me the power to pen down this manuscript in its present shape. Dr.S.SARAVANAN. Dedicated to all my Beloved family members About the author Dr.S.Saravanan M.Com., M.Phil., MBA.,MBA., PGDCA., Ph.D., is a Associate professor in Post Graduate and Research Department of Commerce with Computer Applications at Dr.N.G.P. Arts and Science College, Coimbatore, Tamilnadu, India. He has more than 10 years of experience in teaching and research. An avid researcher having profound knowledge in SPSS statistical research tools, he has published number of research papers in various reputed national and international journals and presented research papers in various conferences. He is also an editor for the Journal of Commerce and Management Research. His research interest has focused on Finance, Marketing and HR. i Chapter- I Introduction 1-16 Definition of research Types of research a. Exploratory/ Formulative Research b. Descriptive Research c. Explanatory Research d. Basic Research e. Applied Research Types of Applied Research i) Action research ii) Impact Assessment Research iii) Evaluation Research The Time Dimension in Research a. Cross-Sectional Research b. Longitudinal Research i. Time series research ii. The panel study iii. A cohort analysis Empirical research Qualitative research Quantitative research Conceptual Research Conclusion-oriented Decision oriented Research One-time Research Diagnostic Research Exploratory Research Historical Research Characteristics of Research ii Chapter- II Research design 17-32 Definitions of research design Steps in planning the research design (1) Determining work involved in the project (2) Estimating costs involved (3) Preparing time schedule (4) Verifying results Importance / utility of research design Feature of good research design Steps of the research process 1: Identify the Problem 2: Review the Literature 3: Clarify the Problem 4: Clearly Define Terms and Concepts 5: Define the Population 6: Develop the Instrumentation Plan 7: Collect Data 8: Analyze the Data Types of Research Design Quantitative Research Designs Qualitative Research Designs iii Chapter-III Types of Variables 33-48 Independent Variable Definition Dependent Variable Definition Continuous variables Discontinuous variables Moderating Variables Extraneous Variables Intervening variable Continuous or Quantitative Variables Interval - scale Variables: Continuous Ordinal Variables Ratio - scale Variables Qualitative or Discrete Variables 1. Nominal variables 2. Ordinal variables 3. Dummy variables from quantitative variables 4. Preference variables 5. Multiple response variables iv Chapter- IV Sampling 49-86 Sample Definition of sampling Purpose of Sampling Sampling Terminology Population or Universe Census Precision Bias Frame Design Random Unit Attribute Variable Statistic Steps in Sampling Process 1. Defining the target population 2. Specifying the sampling frame 3. Specifying the sampling unit 4. Selection of the sampling method 5. Determination of sample size 6. Specifying the sampling plan 7. Selecting the sample Sampling Methods and Techniques v Probability Sampling 1. Simple random sample 2. Systematic random sample 3. Stratified sample 4. Cluster sample Non-Probability Sampling 1. Convenient sample 2. Judgment sample 3. Quota sampling Sample Size Bias and error in sampling Sampling error The interviewer’s effect The respondent effect Knowing the study purpose Induced bias Error Random Sampling Error Non-Sampling error Basic Concepts in Hypothesis Testing Characteristics of Hypothesis Important factors should be considered while frame hypothesis 1. Hypothesis should be clear and specific 2. Hypothesis should be competent of being tested 3. Hypothesis should be limited in scope 4. Hypothesis should be state the variables relationship 5. Hypothesis should be consistent with known facts Types of Hypotheses vi i. Descriptive Hypothesis ii. Relational Hypothesis iii. Null Hypothesis iv. Alternative Hypothesis v. Research Hypothesis The Role of the Hypothesis Characteristics of Testable Hypothesis Hypothesis must be conceptually clear Hypothesis should have empirical referents Hypothesis must be specific Steps in Hypothesis Testing Decision Rules One-Tailed and Two-Tailed Tests vii Chapter - V Tools for Data Collection 87-117 Mailed questionnaire Rating scale Checklist Document schedule/data sheet Schedule for institutions Construction of schedules and questionnaires The process of construction Data need determination Preparation of “Dummy” tables Determination of the respondents’ level Data gathering method decision Instrument drafting Evaluation of the draft instrument Pre-testing Specification of procedures/instructions Designing the format Question Construction Question relevance and content Types of questions to be avoided viii Types of surveys Selecting the survey method Population Issues Sampling issues Question issues Pilot studies and pre-tests Pre-test Meaning Need for Pre-testing Purposes of Pre-testing Advantages and disadvantages of various data collection techniques ix Chapter - VI Data Processing 119-138 Editing Field Editing In-House Editing Editing for Consistency Editing for Completeness Item Non-response Editing Questions Answered out of Order Coding Code Construction Production Coding Data Entries Cleaning Data Data Transformation Indexes and Scales Unidimensionality Index Construction Weighting Scoring and Score Index x Chapter-VII Report Writing 139-164 Types of Report Writing Research Report Writing Business Report Writing Science Report Writing Different Steps in Report Writing Logical analysis of subject matter Preparation of final outline Preparation of Rough Draft Rewriting and Polishing Preparation of final Bibliography Writing the final draft Mechanics of Report Writing Title Page Dedication Acknowledgements Table of Contents Lists of Illustrations Elements of research report Appendix Multiple Choice Questions 166-203 Selected References 204-216 Fundamentals of Research Methodology 1 Chapter- I Introduction Definition of research Types of research a. Exploratory/ Formulative Research b. Descriptive Research c. Explanatory Research d. Basic Research e. Applied Research Types of Applied Research i) Action research ii) Impact Assessment Research iii) Evaluation Research The Time Dimension in Research a. Cross-Sectional Research b. Longitudinal Research i. Time series research ii. The panel study iii. A cohort analysis Empirical research Qualitative research Quantitative research Conceptual Research Conclusion-oriented Decision oriented Research One-time Research Diagnostic Research Exploratory Research Historical Research Characteristics of Research 2 Chapter- I What is Research General image of the research is that it has something to do with the laboratory where scientists are supposedly doing some experiments. Somebody who is interviewing consumers to find out their opinion about the new packaging of milk is also doing research. Research is simply the process of finding solutions to a problem after through study and analysis of the situational factors. It is gathering information needed to answer a question, and thereby help in solving a problem. We do not do study in any haphazard manner. Instead we try to follow a system or a procedure in an organized manner. It is all the more necessary in case we want to repeat the study, or somebody else wants to verify our findings. In the latter case the other person has to follow the same procedure that we followed. Hence not only we have to do the study in a systematic manner but also that system should be known to others. Research can be defined as “a careful study to discover correct information” or “a way of collecting information to facilitate problem solving”. In most simple words, it is “search and search again”. Formal definition as given in Encarta Dictionary is: “A methodical investigation into a subject in order to discover facts, to establish or revise a theory, or to develop a plan of action based on the facts discovered.” Fundamentals of Research Methodology 3 Research can be defined as the search for knowledge, or as any systematic investigation, with an open mind, to establish novel facts, usually using a scientific method. The primary purpose for applied research (as opposed to basic research) is discovering, interpreting, and the development of methods and systems for the advancement of human knowledge on a wide variety of scientific matters of our world and the universe. As per books of Business Research, the definition is: “An organized, systematic, data-based, critical, scientific inquiry or investigation into a specific problem, undertaken with the objective of finding answers or solution to it.” Prof. C.A. Moser defined it as “systematized investigation to give new knowledge about social phenomena and surveys, we call social research”. Rummel defined it as “it is devoted to a study to mankind in his social environment and is concerned with improving his understanding of social orders, groups, institutes and ethics”. M.H. Gopal defined it as “it is scientific analysis of the nature and trends of social phenomena of groups or in general of human behavior so as to formulate broad principles and scientific concepts”. Therefore, research may be considered as an organized, systematic, data based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with the purpose of finding answers or solutions to it. In this way research provides the needed 4 information that guides the planners to make informed decisions to successfully deal with the problems. The information provided could be the result of a careful analysis of data gathered firsthand or of the data that are already available with an organization. Types of Research a. Exploratory/Formulative Research Initial research conducted to clarify the nature of the problem. When a researcher has a limited amount of experience with or knowledge about a research issue, exploratory research is useful preliminary step that helps ensure that a more rigorous, more conclusive future study will not begin with an inadequate understanding of the nature of the management problem. Exploring a new topic or issue in order to learn about it. If the issue was new or the researcher has written little on it, you began at the beginning. This is called exploratory research. The researcher’s goal is to formulate more precise questions that future research can answer. Exploratory research rarely yields definitive answers. It addresses the “what” question: “what is this social activity really about?” It is difficult to conduct because there are few guidelines to follow. Specifically there could be a number of goals of exploratory research. Goals of Exploratory Research 1. Become familiar with the basic facts, setting, and concerns; 2. Develop well grounded picture of the situation; Fundamentals of Research Methodology 5 3. Develop tentative theories; generate new ideas, conjectures, or hypotheses; 4. Determine the feasibility of conducting the study; 5. Formulate questions and refine issues for more systematic inquiry; and 6. Develop techniques and a sense of direction for future research. For exploratory research, the researcher may use different sources for getting information like (1) experience surveys, (2) secondary data analysis, (3) case studies, and (4) pilot studies. As part of the experience survey the researcher tries to contact individuals who are knowledgeable about a particular research problem. This constitutes an informal experience survey. Another economical and quick source of background information is secondary data analysis. It is preliminary review of data collected for another purpose to clarify issues in the early stages of a research effort. The purpose of case study is to obtain information from one or a few situations that are similar to the researcher’s problem situation. A researcher interested in doing a nationwide survey among union workers, may first look at a few local unions to identify the nature of any problems or topics that should be investigated. 6 A pilot study implies that some aspect of the research is done on a small scale. For this purpose focus group discussions could be carried out. b. Descriptive Research Descriptive research presents a picture of the specific details of a situation, social setting, or relationship. The major purpose of descriptive research, as the term implies, is to describe characteristics of a population or phenomenon. Descriptive research seeks to determine the answers to who, what, when, where, and how questions. Labor Force Surveys, Population Census, and Educational Census are examples of such research. Descriptive study offers to the researcher a profile or description of relevant aspects of the phenomena of interest. Look at the class in research methods and try to give its profile – the characteristics of the students. When we start to look at the relationship of the variables, then it may help in diagnosis analysis. In social science and business research we quite often use the term Ex post facto research for descriptive research studies. The main characteristic of this method is that the researcher has no control over the variables; he can only report what has happened or what is happening. Goals of Descriptive Research 1. Describe the situation in terms of its characteristics i.e. provide an accurate profile of a group; 2. Give a verbal or numerical picture (%) of the situation; 3. Present background information; Fundamentals of Research Methodology 7 4. Create a set of categories or classify the information; 5. Clarify sequence, set of stages; and 6. Focus on ‘who,’ ‘what,’ ‘when,’ ‘where,’ and ‘how’ but not why? A great deal of social research is descriptive. Descriptive researchers use most data –gathering techniques – surveys, field research, and content analysis c. Explanatory Research When we encounter an issue that is already known and have a description of it, we might begin to wonder why things are the way they are. The desire to know “why,” to explain, is the purpose of explanatory research. It builds on exploratory and descriptive research and goes on to identify the reasons for something that occurs. Explanatory research looks for causes and reasons. For example, a descriptive research may discover that 10 percent of the parents abuse their children, whereas the explanatory researcher is more interested in learning why parents abuse their children. Goals of Explanatory Research 1. Explain things not just reporting. Why? Elaborate and enrich a theory’s explanation. 2. Determine which of several explanations is best. 3. Determine the accuracy of the theory; test a theory’s predictions or principle. 4. Advance knowledge about underlying process. 8 5. Build and elaborate a theory; elaborate and enrich a theory’s predictions or principle. 6. Extend a theory or principle to new areas, new issues, new topics: 7. Provide evidence to support or refute an explanation or prediction. 8. Test a theory’s predictions or principles d. Basic Research Basic research advances fundamental knowledge about the human world. It focuses on refuting or supporting theories that explain how this world operates, what makes things happen, why social relations are a certain way, and why society changes. Basic research is the source of most new scientific ideas and ways of thinking about the world. It can be exploratory, descriptive, or explanatory; however, explanatory research is the most common. Basic research generates new ideas, principles and theories, which may not be immediately utilized; though are the foundations of modern progress and development in different fields. Fundamental research is mainly concerned with generalisations and with the formulation of a theory. “Gathering knowledge for knowledge’s sake is termed ‘pure’ or ‘basic’ research.” Research concerning some natural phenomenon or relating to pure mathematics are examples of fundamental research. A new idea or fundamental knowledge is not generated only by basic research. Applied research, too, can build new knowledge. Nonetheless, basic research is essential for nourishing the expansion Fundamentals of Research Methodology 9 of knowledge. Researchers at the center of the scientific community conduct most of the basic research. e. Applied Research Applied researchers try to solve specific policy problems or help practitioners accomplish tasks. Theory is less central to them than seeking a solution on a specific problem for a limited setting. Applied research is frequently a descriptive research, and its main strength is its immediate practical use. Applied research is conducted when decision must be made about a specific real-life problem. Applied research encompasses those studies undertaken to answer questions about specific problems or to make decisions about a particular course of action or policy. For example, an organization contemplating a paperless office and a networking system for the company’s personal computers may conduct research to learn the amount of time its employees spend at personal computers in an average week. Research to identify social, economic or political trends that may effect a particular institution or copy research or the marketing research are examples of applied research. Thus, the central aim of applied research is to discover a solution for some pressing practical problems. Thus, the central aim of applied research is to discover a solution for some pressing practical problems. Types of Applied Research Practitioners use several types of applied research. Some of the major ones are: 10 i) Action research: The applied research that treats knowledge as a form of power and abolishes the line between research and social action. Those who are being studied participate in the research process; research incorporates ordinary or popular knowledge; research focuses on power with a goal of empowerment; research seeks to raise consciousness or increase awareness; and research is tied directly to political action. The researchers try to advance a cause or improve conditions by expanding public awareness. They are explicitly political, not value neutral. Because the goal is to improve the conditions of research participants, formal reports, articles, or books become secondary. Action researchers assume that knowledge develops from experience, particularly the experience of social-political action. They also assume that ordinary people can become aware of conditions and learn to take actions that can bring about improvement. ii) Impact Assessment Research: Its purpose is to estimate the likely consequences of a planned change. Such an assessment is used for planning and making choices among alternative policies to make an impact assessment of Narmatha Dam on the environment; to determine changes in housing if a major new highway is built. iii) Evaluation Research: It addresses the question, “Did it work?” The process of establishing value judgment based on evidence about the achievement of the goals of a program. Evaluation research measures the effectiveness of a program, policy, or way of doing something. “Did the program work?” Fundamentals of Research Methodology 11 “Did it achieve its objectives?” Evaluation researchers use several research techniques (survey, field research). Practitioners involved with a policy or program may conduct evaluation research for their own information or at the request of outside decision makers, who sometime place limits on researchers by setting boundaries on what can be studied and determining the outcome of interest. Two types of evaluation research are formative and summative. Formative evaluation is built-in monitoring or continuous feedback on a program used for program management. Summative evaluation looks at final program outcomes. Both are usually necessary. 3. The Time Dimension in Research Another dimension of research is the treatment of time. Some studies give us a snapshot of a single, fixed time point and allow us to analyze it in detail. Other studies provide a moving picture that lets us follow events, people, or sale of products over a period of time. In this way from the angle of time research could be divided into two broad types: a. Cross-Sectional Research. In cross-sectional research, researchers observe at one point in time. Cross-sectional research is usually the simplest and least costly alternative. Its disadvantage is that it cannot capture the change processes. Cross-sectional research can be exploratory, descriptive, or explanatory, but it is most consistent with a descriptive approach to research. 12 b. Longitudinal Research. Researchers using longitudinal research examine features of people or other units at more than one time. It is usually more complex and costly than cross-sectional research but it is also more powerful, especially when researchers seek answers to questions about change. There are three types of longitudinal research: time series, panel, and cohort. i. Time series research is longitudinal study in which the same type of information is collected on a group of people or other units across multiple time periods. Researcher can observe stability or change in the features of the units or can track conditions overtime. One could track the characteristics of students registering in the course on Research Methods over a period of four years i.e. the characteristics (Total, age characteristics, gender distribution, subject distribution, and geographic distribution). Such an analysis could tell us the trends in the characteristic over the four years. ii. The panel study is a powerful type of longitudinal research. In panel study, the researcher observes exactly the same people, group, or organization across time periods. It is a difficult to carry out such study. Tracking people over time is often difficult because some people die or cannot be located. Nevertheless, the results of a well- designed panel study are very valuable. iii. A cohort analysis is similar to the panel study, but rather than observing the exact same people, a category of people who share a similar life experience in a specified time period is studied. The focus is on the cohort, or category, not on specific individuals. Fundamentals of Research Methodology 13 Commonly used cohorts include all people born in the same year (called birth cohorts), all people hired at the same time, all people retire on one or two year time frame, and all people who graduate in a given year. Unlike panel studies, researchers do not have to locate the exact same people for cohort studies. The only need to identify those who experienced a common life event. Empirical research Empirical research relies an experience or observation alone, often without due regard for system and theory. It is data based research, coming up with conclusions which are capable of being verified by observation or experiment. We can also call it as experimental type of research; in such a research it is necessary to get at facts firsthand, at their source, and actively to go about doing certain things to stimulate the production of desired information. In such I research, die researcher must first provide himself with a working hypothesis or guess as to the probable results. He then works to get enough facts (data) to prove or disprove his hypothesis. He then sets up experimental designs which he thinks will manipulate the persons or the materials concerned so as to bring forth the desired information. Such research is thus characterised by the experimenter’s control over the variables under study and his deliberate manipulation of one of them to study its effects. 14 Qualitative research Qualitative research, on the other hand, is concerned with qualitative phenomenon, i.e., phenomena relating to or involving quality or kind. Qualitative research is especially important in the behavioral sciences where the aim is to discover the underlying motives of human behavior. For instance, when we are interested in investigating the reasons for human behavior, we quite often talk of ‘Motivation Research’, an important type of qualitative research. Quantitative research Quantitative research is based on the measurement of quantity or amount. It is applicable to phenomena that can be expressed in terms of quantity Conceptual Research Conceptual research is that related to some abstract idea(s) or theory. It is generally used by philosophers and thinkers to develop new concepts or to reinterpret existing ones. conclusion-oriented and decision oriented Research While doing conclusion oriented research, a researcher is free to pick up a problem, redesign the enquiry as he proceeds and is prepared to conceptualize as he wishes. Decision-oriented research is always for the need of a decision maker and the researcher in this case is not free to embark upon research according to his own inclination. Operations research is an example of decision oriented research since it is a scientific method of providing executive departments with a quantitative basis for decisions regarding operations under their control. Fundamentals of Research Methodology 15 One-time Research – Research confined to a single time period. Diagnostic Research – It is also called clinical research which aims at identifying the causes of a problem, frequency with which it occurs and the possible solutions for it. Exploratory Research – It is the preliminary study of an unfamiliar problem, about which the researcher has little or no knowledge. It is aimed to gain familiarity with the problem, to generate new ideas or to make a precise formulation of the problem. Hence it is also known as formulative research. Historical Research – It is the study of past records and other information sources, with a view to find the origin and development of a phenomenon and to discover the trends in the past, in order to understand the present and to anticipate the future. Characteristics of Research Research is directed towards the solution of a problem. Research is based upon observable experience or empirical evidence. Research demands accurate observation and description. Research involves gathering new data from primary sources or using existing data for a new purpose. Research activities are characterized by carefully designed procedures. 16 Research requires expertise i.e., skill necessary to carryout investigation, search the related literature and to understand and analyze the data gathered. Research is objective and logical – applying every possible test to validate the data collected and conclusions reached. Research involves the quest for answers to unsolved problems. Research requires courage. Research is characterized by patient and unhurried activity. Research is carefully recorded and reported. Fundamentals of Research Methodology 17 Chapter- II Research design Definitions of research design Steps in planning the research design (1) Determining work involved in the project (2) Estimating costs involved (3) Preparing time schedule (4) Verifying results Importance / utility of research design Feature of good research design Steps of the research process 1: Identify the Problem 2: Review the Literature 3: Clarify the Problem 4: Clearly Define Terms and Concepts 5: Define the Population 6: Develop the Instrumentation Plan 7: Collect Data 8: Analyze the Data Types of Research Design Quantitative Research Designs Qualitative Research Designs 18 Chapter- II Research Design An analogy might help. When constructing a building there is no point ordering materials or setting critical dates for completion of project stages until we know what sort of building is being constructed. The first decision is whether we need a high rise office building, a factory for manufacturing machinery, a school, a residential home or an apartment block. Until this is done we cannot sketch a plan, obtain permits, work out a work schedule or order materials. Similarly, social research needs a design or a structure before data collection or analysis can commence. A research design is not just a work plan. A work plan details what has to be done to complete the project. The function of a research design is to ensure that the evidence obtained enables us to answer the initial question as unambiguously as possible. Obtaining relevant evidence entails specifying the type of evidence needed to answer the research question, to test a theory, to evaluate a programme or to accurately describe some phenomenon. In other words, when designing research we need to ask: given this research question (or theory), what type of evidence is needed to answer the question (or test the theory) in a convincing way? Research design `deals with a logical problem and not a logistical problem'. . Before a builder or architect can develop a work plan or Fundamentals of Research Methodology 19 order materials they must first establish the type of building required, its uses and the needs of the occupants. The work plan owes from this. Similarly, in social research the issues of sampling, method of data collection (e.g. questionnaire, observation, and document analysis), and design of questions are all subsidiary to the matter of `What evidence do I need to collect?' Too often researchers design questionnaires or begin interviewing far too early before thinking through what information they require to answer their research questions. Without attending to these research design matters at the beginning, the conclusions drawn will normally be weak and unconvincing and fail to answer the research question. Adopting a skeptical approach to explanations the need for research design stems from a skeptical approach to research and a view that scientific knowledge must always be provisional. The purpose of research design is to reduce the ambiguity of much research evidence. We can always find some evidence consistent with almost any theory. However, we should be skeptical of the evidence, and rather than seeking evidence that is consistent with our theory we should seek evidence that provides a compelling test of the theory. There are two related strategies for doing this: eliminating rival explanations of the evidence and deliberately seeking evidence that could disprove the theory. 20 Definitions of Research Design (1) According to David J . Luck and Ronald S. Rubin, "A research design is the determination and statement of the general research approach or strategy adopted/or the particular project. It is the heart of planning. If the design adheres to the research objective, it will ensure that the client's needs will be served." (2) According to Kerlinger "Research design in the plan, structure and strategy of investigation conceived so as to obtain answers to research questions and to control variance." (3) According to Green and Tull "A research design is the specification of methods and procedures for acquiring the information needed. It is the over-all operational pattern or framework of the project that stipulates what information is to be collected from which source by what procedures." Steps in Planning the Research Design There are four broad steps involved in planning the research design as explained below: (1) Determining work involved in the project: The first step in planning research design is determining the work involved in the project and designing a workable plan to carry out the research work within specific time limit. Fundamentals of Research Methodology 21 The work involved includes the following (a) To formulate the marketing problem (b) To determine information requirement (c) To identify information sources (d) To prepare detailed plan for the execution of research project. This preliminary step indicates the nature and volume of work involved in the research work. Various forms require for research work will be decided and finalised. The sample to be selected for the survey work will also be decided. Staff requirement will also be estimated. Details will be worked out about their training and supervision on field investigators, etc. In addition, the questionnaire will be prepared and tested. This is how the researcher will prepare a blue-print of the research project. According to this blueprint the whole research project will be implemented. The researcher gets clear idea of the work involved in the project through such initial planning of the project. Such planning avoids confusion, misdirection and wastage of time, money and efforts at later stages of research work. The whole research project moves smoothly due to initial planning of the research project. (2) Estimating costs involved The second step in planning research design is estimating the costs involved in the research project. Marketing research projects are costly as the questionnaire is to be prepared in large number of copies, interviewers are to be appointed for data collection and staff 22 will be required for tabulation and analysis of data collected. Finally, experts will be required for drawing conclusions and for writing the research report. The researcher has to estimate the expenditure required for the execution of the project. The sponsoring organisation will approve the research project and make suitable budget provision accordingly. The cost calculation is a complicated job as expenditure on different heads will have to be estimated accurately. The cost of the project also needs to be viewed from the viewpoint of its utility in solving the marketing problem. A comprehensive research study for solving comparatively minor marketing problem will be uneconomical. (3) Preparing time schedule Time factor is important in the execution of the research project. Planning of time schedule is essential at the initial stage. Time calculation relates to the preparation of questionnaire and its pre- testing, training of interviewers, actual survey work, tabulation and analysis of data and finally reports writing. Time requirement of each stage needs to be worked out systematically. Such study will indicate the time requirement of the whole project. Too long period for the completion of research work is undesirable as the conclusions and recommendations may become outdated when actually available. Similarly, time-consuming research projects are not useful for solving urgent marketing problems faced by a company. Preparing time schedule is not adequate in research design. In addition, all operations involved in the research work should be carried out strictly as per time schedule already prepared. If necessary remedial Fundamentals of Research Methodology 23 measures should be adopted in order to avoid any deviation in the time schedule. This brings certainty as regards the completion of the whole research project in time. (4) Verifying results Researcher may create new problems before the sponsoring organisation if the research work is conducted in a faulty manner. Such unreliable study is dangerous as it may create new problems. It is therefore, necessary to keep effective check on the whole research work during the implementing stage. For this suitable provisions need to be made in the research design. After deciding the details of the steps noted above, the background for research design will be ready. Thereafter, the researcher has to prepare the research design of the whole project. He has to present the project design to the sponsoring agency or higher authorities for detailed consideration and approval. The researcher can start the research project (as per design) after securing the necessary approval to the research design prepared. Importance / Utility of Research Design Research design is important as it prepares proper framework within which the research work/activity will be actually carried out Research design acts as a blue print for the conduct of the whole research project. It introduces efficiency in investigation and generates confidence in the final outcome of the study. Research design gives proper direction and time-table to research activity. It keeps adequate check on the research work and ensures its 24 completion within certain time limit. It keeps the whole research project on the right track. Research design avoids possible errors as regards research problem, information requirement and so on. It gives practical orientation to the whole research work and makes it relevant to the marketing problems faced by the sponsoring organisation. Finally, it makes the whole research process compact and result-oriented. A researcher should not go ahead with his research project unless the research design is planned properly. Feature of good research design 1. It specifies the sources and types of information relevant to the research problem 2. It should give smallest experimental error 3. Reliability of data collected and analyzed 4. It should be economical in cost and time 5. It should be flexible 6. It contain the clear statement of the problem 7. It should be appropriate and efficient Steps of the research process Scientific research involves a systematic process that focuses on being objective and gathering a multitude of information for analysis so that Fundamentals of Research Methodology 25 the researcher can come to a conclusion. This process is used in all research and evaluation projects, regardless of the research method (scientific method of inquiry, evaluation research, or action research). The process focuses on testing hunches or ideas in a park and recreation setting through a systematic process. In this process, the study is documented in such a way that another individual can conduct the same study again. This is referred to as replicating the study. Any research done without documenting the study so that others can review the process and results is not an investigation using the scientific research process. The scientific research process is a multiple-step process where the steps are interlinked with the other steps in the process. If changes are made in one step of the process, the researcher must review all the other steps to ensure that the changes are reflected throughout the process. Parks and recreation professionals are often involved in conducting research or evaluation projects within the agency. These professionals need to understand the eight steps of the research process as they apply to conducting a study. Table 2.4 lists the steps of the research process and provides an example of each step for a sample research study. Step 1: Identify the Problem The first step in the process is to identify a problem or develop a research question. The research problem may be something the agency identifies as a problem, some knowledge or information that is needed by the agency, or the desire to identify a recreation trend nationally. In the example in table 2.4, the problem that the agency 26 has identified is childhood obesity, which is a local problem and concern within the community. This serves as the focus of the study Step 2: Review the Literature Now that the problem has been identified, the researcher must learn more about the topic under investigation. To do this, the researcher must review the literature related to the research problem. This step provides foundational knowledge about the problem area. The review of literature also educates the researcher about what studies have been conducted in the past, how these studies were conducted, and the conclusions in the problem area. In the obesity study, the review of literature enables the programmer to discover horrifying statistics related to the long-term effects of childhood obesity in terms of health issues, death rates, and projected medical costs. In addition, the programmer finds several articles and information from the Centers for Disease Control and Prevention that describe the benefits of walking 10,000 steps a day. The information discovered during this step helps the programmer fully understand the magnitude of the problem, recognize the future consequences of obesity, and identify a strategy to combat obesity (i.e., walking). Step 3: Clarify the Problem Many times the initial problem identified in the first step of the process is too large or broad in scope. In step 3 of the process, the researcher clarifies the problem and narrows the scope of the study. This can only be done after the literature has been reviewed. The knowledge gained through the review of literature guides the Fundamentals of Research Methodology 27 researcher in clarifying and narrowing the research project. In the example, the programmer has identified childhood obesity as the problem and the purpose of the study. This topic is very broad and could be studied based on genetics, family environment, diet, exercise, self-confidence, leisure activities, or health issues. All of these areas cannot be investigated in a single study; therefore, the problem and purpose of the study must be more clearly defined. The programmer has decided that the purpose of the study is to determine if walking 10,000 steps a day for three days a week will improve the individual’s health. This purpose is more narrowly focused and researchable than the original problem. Step 4: Clearly Define Terms and Concepts Terms and concepts are words or phrases used in the purpose statement of the study or the description of the study. These items need to be specifically defined as they apply to the study. Terms or concepts often have different definitions depending on who is reading the study. To minimize confusion about what the terms and phrases mean, the researcher must specifically define them for the study. In the obesity study, the concept of “individual’s health” can be defined in hundreds of ways, such as physical, mental, emotional, or spiritual health. For this study, the individual’s health is defined as physical health. The concept of physical health may also be defined and measured in many ways. In this case, the programmer decides to more narrowly define “individual health” to refer to the areas of weight, percentage of body fat, and cholesterol. By defining the terms or concepts more narrowly, the scope of the study is more manageable 28 for the programmer, making it easier to collect the necessary data for the study. This also makes the concepts more understandable to the reader. Step 5: Define the Population Research projects can focus on a specific group of people, facilities, park development, employee evaluations, programs, financial status, marketing efforts, or the integration of technology into the operations. For example, if a researcher wants to examine a specific group of people in the community, the study could examine a specific age group, males or females, people living in a specific geographic area, or a specific ethnic group. Literally thousands of options are available to the researcher to specifically identify the group to study. The research problem and the purpose of the study assist the researcher in identifying the group to involve in the study. In research terms, the group to involve in the study is always called the population. Defining the population assists the researcher in several ways. First, it narrows the scope of the study from a very large population to one that is manageable. Second, the population identifies the group that the researcher’s efforts will be focused on within the study. This helps ensure that the researcher stays on the right path during the study. Finally, by defining the population, the researcher identifies the group that the results will apply to at the conclusion of the study. In the example in table 2.4, the programmer has identified the population of the study as children ages 10 to 12 years. This narrower population makes the study more manageable in terms of time and resources. Fundamentals of Research Methodology 29 Step 6: Develop the Instrumentation Plan The plan for the study is referred to as the instrumentation plan. The instrumentation plan serves as the road map for the entire study, specifying who will participate in the study; how, when, and where data will be collected; and the content of the program. This plan is composed of numerous decisions and considerations that are addressed in chapter 8 of this text. In the obesity study, the researcher has decided to have the children participate in a walking program for six months. The group of participants is called the sample, which is a smaller group selected from the population specified for the study. The study cannot possibly include every 10- to 12-year-old child in the community, so a smaller group is used to represent the population. The researcher develops the plan for the walking program, indicating what data will be collected, when and how the data will be collected, who will collect the data, and how the data will be analyzed. The instrumentation plan specifies all the steps that must be completed for the study. This ensures that the programmer has carefully thought through all these decisions and that she provides a step-by-step plan to be followed in the study. Step 7: Collect Data Once the instrumentation plan is completed, the actual study begins with the collection of data. The collection of data is a critical step in providing the information needed to answer the research question. Every study includes the collection of some type of data whether it is from the literature or from subjects to answer the research question. 30 Data can be collected in the form of words on a survey, with a questionnaire, through observations, or from the literature. In the obesity study, the programmers will be collecting data on the defined variables: weight, percentage of body fat, cholesterol levels, and the number of days the person walked a total of 10,000 steps during the class. The researcher collects these data at the first session and at the last session of the program. These two sets of data are necessary to determine the effect of the walking program on weight, body fat, and cholesterol level. Once the data are collected on the variables, the researcher is ready to move to the final step of the process, which is the data analysis. Step 8: Analyze the Data All the time, effort, and resources dedicated to steps 1 through 7 of the research process culminate in this final step. The researcher finally has data to analyze so that the research question can be answered. In the instrumentation plan, the researcher specified how the data will be analyzed. The researcher now analyzes the data according to the plan. The results of this analysis are then reviewed and summarized in a manner directly related to the research questions. In the obesity study, the researcher compares the measurements of weight, percentage of body fat, and cholesterol that were taken at the first meeting of the subjects to the measurements of the same variables at the final program session. These two sets of data will be analyzed to determine if there was a difference between the first measurement and the Fundamentals of Research Methodology 31 second measurement for each individual in the program. Then, the data will be analyzed to determine if the differences are statistically significant. If the differences are statistically significant, the study validates the theory that was the focus of the study. The results of the study also provide valuable information about one strategy to combat childhood obesity in the community. As you have probably concluded, conducting studies using the eight steps of the scientific research process requires you to dedicate time and effort to the planning process. You cannot conduct a study using the scientific research process when time is limited or the study is done at the last minute. Researchers who do this conduct studies that result in either false conclusions or conclusions that are not of any value to the organization. Types of Research Design Quantitative Research Designs Descriptive Describe phenomena as they exist. Descriptive studies generally take raw data and summarize it in a useable form. Can also be qualitative in nature if the sample size is small and data are collected from questionnaires, interviews or observations. Experimental The art of planning and implementing an experiment in which the research has control over some of the conditions where the study takes place and control over some aspects of the independent variable(s) (presumed cause or variable used to predict another variable) 32 Quasi- experimental A form of experimental research. One in which the researcher cannot control at least one of the three elements of an experimental design: Environment Intervention (program or practice) Assignment to experimental and control groups Qualitative Research Designs Historical Collection and evaluation of data related to past events that are used to describe causes, effects and trends that may explain present or future events. Data are often archival. Data includes interviews. Ethnographic The collection of extensive narrative data over an extended period of time in natural settings to gain insights about other types of research. Data are collected through observations at particular points of time over a sustained period. Data include observations, records and interpretations of what is seen. Case Studies An in-depth study of an individual group, institution, organization or program. Data include interviews, field notes of observations, archival data and biographical data. Fundamentals of Research Methodology 33 Chapter-III Types of Variables Independent Variable Definition Dependent Variable Definition Continuous variables Discontinuous variables Moderating Variables Extraneous Variables Intervening variable Continuous or Quantitative Variables Interval - scale Variables Continuous Ordinal Variables Ratio - scale Variables Qualitative or Discrete Variables 1. Nominal variables 2. Ordinal variables 3. Dummy variables from quantitative variables 4. Preference variables 5. Multiple response variables 34 Chapter-III Variables and Types of Variables Variable is central idea in research. Simply defined, variable is a concept that varies. There are two types of concepts: those that refer to a fixed phenomenon and those that vary in quantity, intensity, or amount (e.g. amount of education). The second type of concept and measures of the concept are variables. A variable is defined as anything that varies or changes in value. Variables take on two or more values. Because variable represents a quality that can exhibit differences in value, usually magnitude or strength, it may be said that a variable generally is anything that may assume different numerical or categorical values. Once you begin to look for them, you will see variables everywhere. For example gender is a variable; it can take two values: male or female. Marital status is a variable; it can take on values of never married, single, married, divorced, or widowed. Family income is a variable; it can take on values from zero to billions of Rupees. A person’s attitude toward women empowerment is variable; it can range from highly favorable to highly unfavorable. In this way the variation can be in quantity, intensity, amount, or type; the examples can be production units, absenteeism, gender, religion, motivation, grade, and age. A variable may be situation specific; for example gender is a variable but if in a particular situation like a class of Fundamentals of Research Methodology 35 Research Methods if there are only female students, then in this situation gender will not be considered as a variable. Independent Variable Definition An independent variable, sometimes called an experimental or predictor variable, is a variable that is being manipulated in an experiment in order to observe the effect on a dependent variable, sometimes called an outcome variable. The independent variable is the variable that is manipulated by the researcher. The independent variable is something that is hypothesized to influence the dependent variable. The researcher determines for the participant what level or condition of the independent variable that the participant in the experiment receives. For example, each participant in the experiment may be randomly assigned to either an experimental condition or the control condition. Dependent Variable Definition The dependent variable is simply that, a variable that is dependent on an independent variable(s).The dependent variable is the variable that is simply measured by the researcher. It is the variable that reflects the influence of the independent variable. For example, the dependent variable would be the variable that is influenced by being randomly assigned to either an experimental condition or a control condition. 36 Examples of Independent Variable and Examples of Dependent Variable If one were to measure the influence of different quantities of fertilizer on plant growth, the independent variable would be the amount of fertilizer used (the changing factor of the experiment). The dependent variables would be the growth in height and/or mass of the plant (the factors that are influenced in the experiment) and the controlled variables would be the type of plant, the type of fertilizer, the amount of sunlight the plant gets, the size of the pots, etc. (the factors that would otherwise influence the dependent variable if they were not controlled). In a study of how different doses of a drug affect the severity of symptoms, a researcher could compare the frequency and intensity of symptoms (the dependent variables) when different doses (the independent variable) are administered, and attempt to draw a conclusion. In order to clarify the concepts of independent variable and dependent variable, it is important to provide examples. Imagine that you wished to know whether listening to music would increase productivity in the workplace. You randomly assign each participant in this experiment to either an experimental condition or a control condition. In the experimental condition, participants listen to music while they work. In the control condition, the participants do not listen to music while they work. In this example, listening to music Fundamentals of Research Methodology 37 vs. not listening to music is the independent variable. The dependent variable in this example is productivity. Continuous variables Variables have different properties and to these properties we assign numerical values. If the values of a variable can be divided into fractions then we call it a continuous variable. Such a variable can take infinite number of values. Income, temperature, age, or a test score are examples of continuous variables. These variables may take on values within a given range or, in some cases, an infinite set. Discontinuous variables Any variable that has a limited number of distinct values and which cannot be divided into fractions, is a discontinuous variable. Such a variable is also called as categorical variable or classificatory variable, or discrete variable. Some variables have only two values, reflecting the presence or absence of a property: employed- unemployed or male-female have two values. These variables are referred to as dichotomous. There are others that can take added categories such as the demographic variables of race, religion. All such variables that produce data that fit into categories are said to be discrete/categorical/classificatory, since only certain values are possible. Let we assume a variable related to automobile, let say if we assigned a value for Honda =5 and Chevrolet =6 so no option if available for 5.5 because we cannot divide the value into fractions. 38 Moderating Variables A moderating variable is one that has a strong contingent effect on the independent variable-dependent variable relationship. That is, the presence of a third variable (the moderating variable) modifies the original relationship between the independent and the dependent variable. For example, a strong relationship has been observed between the quality of library facilities (X) and the performance of the students (Y). Although this relationship is supposed to be true generally, it is nevertheless contingent on the interest and inclination of the students. It means that only those students who have the interest and inclination to use the library will show improved performance in their studies. In this relationship interest and inclination is moderating variable i.e. which moderates the strength of the association between X and Y variables. Extraneous Variables Extraneous Variables are undesirable variables that influence the relationship between the variables that an experimenter is examining. Another way to think of this, is that these are variables the influence the outcome of an experiment, though they are not the variables that are actually of interest. These variables are undesirable because they add error to an experiment. A major goal in research design is to decrease or control the influence of extraneous variables as much as possible. Fundamentals of Research Methodology 39 For example, let’s say that an educational psychologist has developed a new learning strategy and is interested in examining the effectiveness of this strategy. The experimenter randomly assigns students to two groups. All of the students study text materials on a biology topic for thirty minutes. One group uses the new strategy and the other uses a strategy of their choice. Then all students complete a test over the materials. One obvious confounding variable in this case would be pre-knowledge of the biology topic that was studied. This variable will most likely influence student scores, regardless of which strategy they use. Because of this extraneous variable (and surely others) there will be some spread within each of the groups. It would be better, of course, if all students came in with the exact same pre-knowledge. However, the experimenter has taken an important step to greatly increase the chances that, at least, the extraneous variable will add error variance equivalently between the two groups. That is, the experimenter randomly assigned students to the two groups. Intervening variable A variable, used in the process of explaining an observed relationship between an independent and dependent variable(s), A basic causal relationship requires only independent and dependent variable. A third type of variable, the intervening variable, appears in more complex causal relationships. It comes between the independent and dependent variables and shows the link or mechanism between them. Advances in knowledge depend not only on documenting cause and effect relationship but also on specifying the mechanisms that 40 account for the causal relation. In a sense, the intervening variable acts as a dependent variable with respect to independent variable and acts as an independent variable toward the dependent variable. For example X is age and Y is reading ability, the causal relationship between X and Y might be explained by the intervening variable “Z”, say education, which explains the X → Y link. Hence X is an indirect cause of Y through the intervening variable Z: “Z” predicts Y but is simultaneously predicted by X. Continuous or Quantitative Variables Continuous variables can be classified into three categories: Interval - scale Variables Interval scale data has order and equal intervals. Interval scale variables are measured on a linear scale, and can take on positive or negative values. It is assumed that the intervals keep the same importance throughout the scale. They allow us not only to rank order the items that are measured but also to quantify and compare the magnitudes of differences between them. We can say that the temperature of 40°C is higher than 30°C, and an increase from 20°C to 40°C is twice as much as the increase from 30°C to 40°C. Counts are interval scale measurements, such as counts of publications or citations, years of education, etc. Fundamentals of Research Methodology 41 Continuous Ordinal Variables They occur when the measurements are continuous, but one is not certain whether they are on a linear scale, the only trustworthy information being the rank order of the observations. For example, if a scale is transformed by an exponential, logarithmic or any other nonlinear monotonic transformation, it loses its interval - scale property. Here, it would be expedient to replace the observations by their ranks. Ratio - scale Variables These are continuous positive measurements on a nonlinear scale. A typical example is the growth of bacterial population (say, with a growth function Ae Bt .). In this model, equal time intervals multiply the population by the same ratio. Ratio data are also interval data, but they are not measured on a linear scale. . With interval data, one can perform logical operations, add, and subtract, but one cannot multiply or divide. For instance, if a liquid is at 40 degrees and we add 10 degrees, it will be 50 degrees. However, a liquid at 40 degrees does not have twice the temperature of a liquid at 20 degrees because 0 degrees does not represent "no temperature" -- to multiply or divide in this way we would have to use the Kelvin temperature scale, with a true zero point (0 degrees Kelvin = -273.15 degrees Celsius). In social sciences, the issue of "true zero" rarely arises, but one should be aware of the statistical issues involved. 42 There are three different ways to handle the ratio-scaled variables. Simply as interval scale variables. However this procedure should be avoided as it can distort the results. As continuous ordinal scale. By transforming the data (for example, logarithmic transformation) and then treating the results as interval scale variables. Qualitative or Discrete Variables Discrete variables are also called categorical variables. A discrete variable, X, can take on a finite number of numerical values, categories or codes. Discrete variables can be classified into the following categories: 1. Nominal variables 2. Ordinal variables 3. Dummy variables from quantitative variables 4. Preference variables 5. Multiple response variables 1. Nominal Variables Nominal variables allow for only qualitative classification. That is, they can be measured only in terms of whether the individual items belong to certain distinct categories, but we cannot quantify or even rank order the categories: Nominal data has no order, and the assignment of numbers to categories is purely arbitrary. Because of lack of order or equal intervals, Fundamentals of Research Methodology 43 one cannot perform arithmetic (+, -, /, *) or logical operations (>, <, =) on the nominal data. Typical examples of such variables are: Dichotomous variables are nominal variables which have only two categories or levels. For example, if we were looking at gender, we would most probably categorize somebody as either "male" or "female". This is an example of a dichotomous variable (and also a nominal variable). Another example might be if we asked a person if they owned a mobile phone. Here, we may categorise mobile phone ownership as either "Yes" or "No". In the real estate agent example, if type of property had been classified as either residential or commercial then "type of property" would be a dichotomous variable. Gender: 1.Male 2. Female Marital Status: 1.Unmarried 2.Married 3.Divorcee 4. Widower Educational qualifications 1.illiterate 2.Primary school level 3.Higher secondary level 4.College level 44 2. Ordinal Variables A discrete ordinal variable is a nominal variable, but its different states are ordered in a meaningful sequence. Ordinal data has order, but the intervals between scale points may be uneven. Because of lack of equal distances, arithmetic operations are impossible, but logical operations can be performed on the ordinal data. A typical example of an ordinal variable is the socio-economic status of families. We know 'upper middle' is higher than 'middle' but we cannot say 'how much higher'. Ordinal variables are quite useful for subjective assessment of 'quality; importance or relevance'. Ordinal scale data are very frequently used in social and behavioral research. Almost all opinion surveys today request answers on three-, five-, or seven- point scales. Such data are not appropriate for analysis by classical techniques, because the numbers are comparable only in terms of relative magnitude, not actual magnitude. Consider for example a questionnaire item on the time involvement of scientists in the 'perception and identification of research problems'. The respondents were asked to indicate their involvement by selecting one of the following codes: 1 =Very low or nil, 2 =Low, 3 =Medium, 4 = Great, 5 =Very great Here, the variable 'Time Involvement' is an ordinal variable with 5 states. Fundamentals of Research Methodology 45 Ordinal variables often cause confusion in data analysis. Some statisticians treat them as nominal variables. Other statisticians treat them as interval scale variables, assuming that the underlying scale is continuous, but because of the lack of a sophisticated instrument, they could not be measured on an interval scale. 2. Dummy Variables from Quantitative Variables A quantitative variable can be transformed into a categorical variable, called a dummy variable by recoding the values. Consider the following example: the quantitative variable Age can be classified into five intervals. The values of the associated categorical variable, called dummy variables, are 1, 2,3,4,5: [Up to 25] 1 [25, 40 ] 2 [40, 50] 3 [50, 60] 4 [Above 60] 5 3. Preference Variables Preference variables are specific discrete variables, whose values are either in a decreasing or increasing order. For example, in a survey, a respondent may be asked to indicate the importance of the following nine sources of information in his research and development work, by using the code [1] for the 46 most important source and [9] for the least important source: give the order of preference. 1. Literature published in the country 2. Literature published abroad 3. Scientific abstracts 4. Unpublished reports, material, etc. 5. Discussions with colleagues within the research unit 6. Discussions with colleagues outside the research unit but within institution 7. Discussions with colleagues outside the institution 8. Scientific meetings in the country 9. Scientific meetings abroad Note that preference data are also ordinal. The interval distance from the first preference to the second preference is not the same as, for example, from the sixth to the seventh preference. 1. Multiple Response Variables Multiple response variables are those, which can assume more than one value. A typical example is a survey questionnaire about the use of computers in research. The respondents were asked to indicate the purpose(s) for which they use computers in their research work. The respondents could score more than one category. Fundamentals of Research Methodology 47 1. Statistical analysis 2. Lab automation/ process control 3. Data base management, storage and retrieval 4. Modeling and simulation 5. Scientific and engineering calculations 6. Computer aided design (CAD) 7. Communication and networking 8. Graphics FOUR SCALES COMPARED Nominal Original Interval Ratio Classification but no order, distance or origin Classification but order but no distance or unique origin Classification, ordered and distance but no unique origin Classification, order, distance and unique origin Determination of equality Determination of greater or lesser value Determination of equality of intervals or differences Determination of equality of ratios Only Label Ranks, Rating and Grade equal grouping Weight, height Gender (male, female) Doneness of meat, (well, medium well, medium rare, rare) temperature in degrees Age in years 48 Nominal Original Interval Ratio Counting Frequency Distribution Addition/subtraction but no multiplication or division All functions Black & While AAA, BBB, CCC personality measure Can say no measurable value like zero sales Religion Levels, one-star & 4-star Mean, range, variance, standard deviation Annual Income Fundamentals of Research Methodology 49 Chapter- IV Sampling Sample Definition of sampling Purpose of Sampling Sampling Terminology Population or Universe Census Precision Bias Frame Design Random Unit Attribute Variable Statistic Steps in Sampling Process 1. Defining the target population 2. Specifying the sampling frame 3. Specifying the sampling unit 4. Selection of the sampling method 5. Determination of sample size 6. Specifying the sampling plan 7. Selecting the sample Sampling Methods and Techniques 50 Probability Sampling 1. Simple random sample 2. Systematic random sample 3. Stratified sample 4. Cluster sample Non-Probability Sampling 1. Convenient sample 2. Judgment sample 3. Quota sampling Sample Size Bias and error in sampling Sampling error The interviewer’s effect The respondent effect Knowing the study purpose Induced bias Error Random Sampling Error Non-Sampling error Basic Concepts in Hypothesis Testing Characteristics of Hypothesis Important factors should be considered while frame hypothesis 1. Hypothesis should be clear and specific 2. Hypothesis should be competent of being tested 3. Hypothesis should be limited in scope 4. Hypothesis should be state the variables relationship 5. Hypothesis should be consistent with known facts Fundamentals of Research Methodology 51 Types of Hypotheses i. Descriptive Hypothesis ii. Relational Hypothesis iii. Null Hypothesis iv. Alternative Hypothesis v. Research Hypothesis The Role of the Hypothesis Characteristics of Testable Hypothesis Hypothesis must be conceptually clear Hypothesis should have empirical referents Hypothesis must be specific Steps in Hypothesis Testing Decision Rules One-Tailed and Two-Tailed Tests 52 Chapter- IV Sampling Sample A sample is a finite part of a statistical population whose properties are studied to gain information about the whole. When dealing with people, it can be defined as a set of respondents (people) selected from a larger population for the purpose of a survey. A population is a group of individuals, persons, objects, or items from which samples are taken for measurement for example a population of presidents or professors, books or students. Sampling Sampling is the act, process, or technique of selecting a suitable sample, or a representative part of a population for the purpose of determining parameters or characteristics of the whole population. Definition of sampling Good and Hatt defined, “A sample is a smaller representation of a large whole”. Sampling can be defined as selecting part of the elements in a population. It results in the fact that, conclusions from the sample may be extended to that about the entire population. Fundamentals of Research Methodology 53 Purpose of Sampling To draw conclusions about populations from samples, we must use inferential statistics which enables us to determine a population`s characteristics by directly observing only a portion (or sample) of the population. We obtain a sample rather than a complete enumeration (a census) of the population for many reasons. Obviously, it is cheaper to observe a part rather than the whole, but we should prepare ourselves to cope with the dangers of using samples. Sampling Terminology Population OR Universe The entire aggregation of items from which samples can be drawn is known as a population. In sampling, the population may refer to the units, from which the sample is drawn. Population or populations of interest are interchangeable terms. The term “unit” is used, as in a business research process; samples are not necessarily people all the time. A population of interest may be the universe of nations or cities. This is one of the first things the analyst needs to define properly while conducting a business research. Therefore, population, contrary to its general notion as a nation’s entire population has a much broader meaning in sampling. “N” represents the size of the population. Census A complete study of all the elements present in the population is known as a census. It is a time consuming and costly process and is, therefore, seldom a popular with researchers. The general notion that 54 a census generates more accurate data than sampling is not always true. Limitations include failure in generating a complete and accurate list of all the members of the population and refusal of the elements to provide information. The national population census is an example of census survey. Precision Precision is a measure of how close an estimate is expected to be, to the true value of a parameter. Precision is a measure of similarity. Precision is usually expressed in terms of imprecision and related to the standard error of the estimate. Less precision is reflected by a larger standard error. Bias Bias is the term refers to how far the average statistic lies from the parameter it is estimating, that is, the error, which arises when estimating a quantity. Errors from chance will cancel each other out in the long run, those from bias will not. Bias can take different forms. Frame The frame describes the population in terms of sampling units. It may often be a geographical area, such as a list of city blocks or counties. Fundamentals of Research Methodology 55 Design The design describes the method by which the sample is chosen. Random A mathematical term “random” means that every element in the total population has an equal chance or probability of being chosen for the sample and that each of these elements is independent of the other. Unit Any “population” or “universe” should contain some specifications in terms of content units, extend and time. Attribute It is a characteristic possessive trait of an element of a population. For example, if in a class of 35 students 15 had dark hair, then we could say that 15 students possess the given attribute. Variable A variable can always be transformed into an attribute by a broad grouping the variable. Statistic Statistic refers to the value of a variable calculated from a sample taken out of a universe or population. The characteristics of a sample are called a statistic. 56 Steps in Sampling Process An operational sampling process can be divided into seven steps as given below: 1. Defining the target population. 2. Specifying the sampling frame. 3. Specifying the sampling unit. 4. Selection of the sampling method. 5. Determination of sample size. 6. Specifying the sampling plan. 7. Selecting the sample. 1. Defining the Target Population Defining the population of interest, for business research, is the first step in sampling process. In general, target population is defined in terms of element, sampling unit, extent, and time frame. The definition should be in line with the objectives of the research study. For example, if a kitchen appliances firm wants to conduct a survey to ascertain the demand for its micro ovens, it may define the population as ‘all women above the age of 20 who cook (assuming that very few men cook)’. However this definition is too broad and will include every household in the country, in the population that is to be covered by the survey. Therefore the definition can be further refined and defined at the sampling unit level, that, all women above the age 20, who cook and whose monthly household income exceeds Rs.20,000. This reduces the target population size and makes the research more focused. The population definition can be refined further by specifying the area from where the researcher has to draw his sample, that is, households located in Hyderabad. Fundamentals of Research Methodology 57 A well defined population reduces the probability of including the respondents who do not fit the research objective of the company. For ex, if the population is defined as all women above the age of 20, the researcher may end up taking the opinions of a large number of women who cannot afford to buy a micro oven. 2. Specifying the Sampling Frame Once the definition of the population is clear a researcher should decide on the sampling frame. A sampling frame is the list of elements from which the sample may be drawn. Continuing with the micro oven ex, an ideal sampling frame would be a database that contains all the households that have a monthly income above Rs.20, 000. However, in practice it is difficult to get an exhaustive sampling frame that exactly fits the requirements of a particular research. In general, researchers use easily available sampling frames like telephone directories and lists of credit card and mobile phone users. Various private players provide databases developed along various demographic and economic variables. Sometimes, maps and aerial pictures are also used as sampling frames. Whatever may be the case, an ideal sampling frame is one that entire population and lists the names of its elements only once. A sampling frame error pops up when the sampling frame does not accurately represent the total population or when some elements of the population are missing another drawback in the sampling frame is over –representation. A telephone directory can be over represented by names/household that has two or more connections. 58 3. Specifying the Sampling Unit A sampling unit is a basic unit that contains a single element or a group of elements of the population to be sampled. In this case, a household becomes a sampling unit and all women above the age of 20 years living in that particular house become the sampling elements. If it is possible to identify the exact target audience of the business research, every individual element would be a sampling unit. This would present a case of primary sampling unit. However, a convenient and better means of sampling would be to select households as the sampling unit and interview all females above 20 years, who cook. This would present a case of secondary sampling unit. 4. Selection of the Sampling Method The sampling method outlines the way in which the sample units are to be selected. The choice of the sampling method is influenced by the objectives of the business research, availability of financial resources, time constraints, and the nature of the problem to be investigated. All sampling methods can be grouped under two distinct heads, that is, probability and non-probability sampling. 5. Determination of Sample Size The sample size plays a crucial role in the sampling process. There are various ways of classifying the techniques used in determining the sample size. A couple those hold primary importance and are worth mentioning are whether the technique deals with fixed or Fundamentals of Research Methodology 59 sequential sampling and whether its logic is based on traditional or Bayesian methods. In non-probability sampling procedures, the allocation of budget, thumb rules and number of sub groups to be analyzed, importance of the decision, number of variables, nature of analysis, incidence rates, and completion rates play a major role in sample size determination. In the case of probability sampling, however, formulas are used to calculate the sample size after the levels of acceptable error and level of confidence are specified. 6. Specifying the Sampling Plan In this step, the specifications and decisions regarding the implementation of the research process are outlined. Suppose, blocks in a city are the sampling units and the households are the sampling elements. This step outlines the modus operandi of the sampling plan in identifying houses based on specified characteristics. It includes issues like how is the interviewer going to take a systematic sample of the houses. What should the interviewer do when a house is vacant? What is the recontact procedure for respondents who were unavailable? All these and many other questions need to be answered for the smooth functioning of the research process. These are guide lines that would help the researcher in every step of the process. As the interviewers and their co-workers will be on field duty of most of the time, a proper specification of the sampling plans would make their work easy and they would not have to revert to their seniors when faced with operational problems. 60 7. Selecting the Sample This is the final step in the sampling process, where the actual selection of the sample elements is carried out. At this stage, it is necessary that the interviewers stick to the rules outlined for the smooth implementation of the business research. This step involves implementing the sampling plan to select the sampling plan to select a sample required for the survey. Sampling methods and techniques There are many different types of sampling technique. The most popular sampling techniques are below: Sampling Method Definition Uses Limitations Cluster Sampling Units in the population can often be found in certain geographic groups or "clusters" (e.g. primary school children in Derbyshire. A random sample of clusters is taken, then all units within the cluster are examined) Quick & easy; does not require complete population information; good for face- to-face surveys Expensive if the clusters are large; greater risk of sampling error Convenience Sampling Uses those who are willing to volunteer Readily available; large amount of information can be gathered quickly Cannot extrapolate from sample to infer about the population; prone to volunteer bias Fundamentals of Research Methodology 61 J udgment Sampling A deliberate choice of a sample - the opposite of random Good for providing illustrative examples or case studies Very prone to bias; samples often small; cannot extrapolate from sample Quota Sampling Aim is to obtain a sample that is "representative" of the overall population; the population is divided ("stratified") by the most important variables (e.g. income,. age, location) and a required quota sample is drawn from each stratum Quick & easy way of obtaining a sample Not random, so still some risk of bias; need to understand the population to be able to identify the basis of stratification Simply Random Sampling Ensures that every member of the population has an equal chance of selection Simply to design and interpret; can calculate estimate of the population and the sampling error Need a complete and accurate population listing; may not be practical if the sample requires lots of small visits all over the country Systematic Sampling After randomly selecting a starting point from the population, between 1 and "n", every nth unit is selected, where n equals the population size divided by the sample size Easier to extract the sample than via simple random; ensures sample is spread across the population Can be costly and time- consuming if the sample is not conveniently located 62 Probability Sampling A simple random sample A simple random sample is obtained by choosing elementary units in search a way that each unit in the population has an equal chance of being selected. A simple random sample is free from sampling bias. However, using a random number table to choose the elementary units can be cumbersome. If the sample is to be collected by a person untrained in statistics, then instructions may be misinterpreted and selections may be made improperly. Instead of using a least of random numbers, data collection can be simplified by selecting say every 10th or 100th unit after the first unit has been chosen randomly. Such a procedure is called systematic random sampling. A systematic random sample A systematic random sample is obtained by selecting one unit on a random basis and choosing additional elementary units at evenly Fundamentals of Research Methodology 63 spaced intervals until the desired number of units is obtained. For example, there are 100 students in your class. You want a sample of 20 from these 100 and you have their names listed on a piece of paper may be in an alphabetical order. If you choose to use systematic random sampling, divide 100 by 20, you will get 5. Randomly select any number between 1 and five. Suppose the number you have picked is 4, that will be your starting number. So student number 4 has been selected. From there you will select every 5th name until you reach the last one, number one hundred. You will end up with 20 selected students. A stratified sample A stratified sample is obtained by independently selecting a separate simple random sample from each population stratum. A population can be divided into different groups may be based on some characteristic or variable like income of education. Like any body with ten years of education will be in group A, between 10 and 20 group B and between 20 and 30 group C. These groups are referred to as strata. Researcher can then randomly select from each stratum a given number of units which may be based on proportion like if group A has 100 persons while group B has 50, and C has 30 researcher may decide you will take 10% of each. So researcher end up with 10 from group A, 5 from group B and 3 from group C. 64 A cluster sample A cluster sample is obtained by selecting clusters from the population on the basis of simple random sampling. The sample comprises a census of each random cluster selected. For example, a cluster may be some thing like a village or a school, a state. So you decide all the elementary schools in Newyork State are clusters. You want 20 schools selected. You can use simple or systematic random sampling to select the schools, and then every school selected becomes a cluster. If you interest to interview teachers on their opinion of some new program which has been introduced, then all the teachers in a cluster must be interviewed. Though it is very economical cluster sampling is very susceptible to sampling bias. Like for the above case, you are likely to get similar responses from teachers in one school due to the fact that they interact with one another. Non-Probability Sampling The convenient sample A convenience sample results when the more convenient elementary units are chosen from a population for observation. The judgment sample A judgment sample is obtained according to the discretion of someone who is familiar with the relevant characteristics of the population. Fundamentals of Research Methodology 65 Quota sampling A quota sample is one in which the interviewer is instructed to collect information from an assigned number, or quota, of individuals in each of several groups-the groups being specified as to age, sex, income, or other characteristics much like the strata in stratified sampling. Sample Size Before deciding how large a sample should be, researcher has to define the study population. For example, all children below age three in particular city. Then determine sampling frame which could be a list of all the children below three as recorded by city. Then struggle with the sample size. The question of how large a sample should be is a difficult one. Sample size can be determined by various constraints. For example, the available funding may prespecify the sample size. When research costs are fixed, a useful rule of thumb is to spend about one half of the total amount for data collection and the other half for data analysis. This constraint influences the sample size as well as sample design and data collection procedures. In general, sample size depends on the nature of the analysis to be performed, the desired precision of the estimates one wishes to achieve, the kind and number of comparisons that will be made, the number of variables that have to be examined simultaneously and how heterogeneous a universe is sampled. For example, if the key analysis of a randomized experiment consists of computing averages 66 for experimental and controls in a project and comparing differences, then a sample under 100 might be adequate, assuming that other statistical assumptions hold. In non-experimental research, most often, relevant variables have to be controlled statistically because groups differ by factors other than chance. More technical considerations suggest that the required sample size is a function of the precision of the estimates one wishes to achieve, the variability or variance, one expects to find in the population and the statistical level of confidence one wishes to use. Deciding on a sample size for qualitative inquiry can be even more difficult than quantitative because there are no definite rules to be followed. It will depend on what you want to know, the purpose of the inquiry, what is at stake, what will be useful, what will have credibility and what can be done with available time and resources. With fixed a resource which is always the case, researcher can choose to study one specific phenomenon in depth with a smaller sample size or a bigger sample size when seeking breadth. In purposeful sampling, the sample should be judged on the basis of the purpose and rationale for each study and the sampling strategy used to achieve the studies purpose. The validity, meaningfulness, and insights generated from qualitative inquiry have more to do with the information-richness of the cases selected and the observational/analytical capabilities of the researcher than with sample size. Fundamentals of Research Methodology 67 For any sample design deciding upon the appropriate sample size will depend on several key factors (1) No estimate taken from a sample is expected to be exact: Any assumptions about the overall population based on the results of a sample will have an attached margin of error. (2) To lower the margin of error usually requires a larger sample size. The amount of variability in the population (i.e. the range of values or opinions) will also affect accuracy and therefore the size of sample. (3) The confidence level is the likelihood that the results obtained from the sample lie within a required precision. The higher the confidence level that is the more certain researcher wishes to be that the results are not atypical. Statisticians often use a 95 per cent confidence level to provide strong conclusions. (4) Population size does not normally affect sample size. In fact the larger the populations size the lower the proportion of that population that needs to be sampled to be representative. It is only when the proposed sample size is more than 5 per cent of the population that the population size becomes part of the formulae to calculate the sample size. Bias and error in sampling A sample is expected to mirror the population from which it comes; however, there is no guarantee that any sample will be precisely representative of the population from which it comes. Chance may 68 dictate that a disproportionate number of untypical observations will be made like for the case of testing fuses, the sample of fuses may consist of more or less faulty fuses than the real population proportion of faulty cases. In practice, it is rarely known when a sample is unrepresentative and should be discarded. Sampling error What can make a sample unrepresentative of its population? One of the most frequent causes is sampling error. Sampling error comprises the differences between the sample and the population that are due solely to the particular units that happen to have been selected. For example, suppose that a sample of 100 women are measured in a particular city and are all found to be taller than six feet. It is very clear even without any statistical prove that this would be a highly unrepresentative sample leading to invalid conclusions. This is a very unlikely occurrence because naturally such rare cases are widely distributed among the population. But it can occur. Luckily, this is a very obvious error and can be elected very easily. The more dangerous error is the less obvious sampling error against which nature offers very little protection. An example would be like a sample in which the average height is overstated by only one inch or two rather than one foot which is more obvious. It is the unobvious error that is of much concern. Fundamentals of Research Methodology 69 There are two basic causes for sampling error. One is chance: That is the error that occurs just because of bad luck. This may result in untypical choices. Unusual units in a population do exist and there is always a possibility that an abnormally large number of them will be chosen. Sampling bias is a tendency to favour the selection of units that have particular characteristics. Sampling bias is usually the result of a poor sampling plan. The most notable is the bias of non response when for some reason some units have no chance of appearing in the sample. For example, take a hypothetical case where a survey was conducted recently by Cornell Graduate School to find out the level of stress that graduate students were going through. A mail questionnaire was sent to 100 randomly selected graduate students. Only 52 responded and the results were that students were not under stress at that time when the actual case was that it was the highest time of stress for all students except those who were writing their thesis at their own pace. A means of selecting the units of analysis must be designed to avoid the more obvious forms of bias. Another example would be where researcher would like to know the average income of some community and researcher decide to use the telephone numbers to select a sample of the total population in a locality where only the rich and middle class households have telephone lines. Researcher will end up with high average income which will lead to the wrong policy decisions. 70 The interviewer’s effect No two interviewers are alike and the same person may provide different answers to different interviewers. The manner in which a question is formulated can also result in inaccurate responses. Individuals tend to provide false answers to particular questions. For example, some people want to feel younger or older for some reason known to them. If researcher ask such a person their age in years, it is easier for the individual just to lie to researcher by over stating their age by one or more years than it is if researcher asked which year they were born since it will require a bit of quick arithmetic to give a false date and a date of birth will definitely be more accurate. The respondent effect Respondents might also give incorrect answers to impress the interviewer. This type of error is the most difficult to prevent because it results from out right deceit on the part of the responded. For example a research made in 1995, a researcher witnessed in his study in which he was asked farmers how much maize they harvested in the year 1995. In most cases, the men tended to lie by saying a figure which is the recommended expected yield that is 25 bags per acre. The responses from men looked so uniform that he became suspicious. I compared with the responses of the wives of these men and their responses were all different. To decide which one was right, whenever possible he could in a tactful way verify with an older son or daughter. It is important to acknowledge that certain psychological Fundamentals of Research Methodology 71 factors induce incorrect responses and great care must be taken to design a study that minimizes their effect. Knowing the study purpose Knowing why a study is being conducted may create incorrect responses. A classic example is the question: What is your income? If a government agency is asking, a different figure may be provided than the respondent would give on an application for a home mortgage. One way to guard against such bias is to camouflage the study`s goals; Another remedy is to make the questions very specific, allowing no room for personal interpretation. For example, "Where are you employed?" could be followed by "What is your salary?" and "Do you have any extra jobs?" A sequence of such questions may produce more accurate information. Induced bias Finally, it should be noted that the personal prejudices of either the designer of the study or the data collector may tend to induce bias. In designing a questionnaire, questions may be slanted in such a way that a particular response will be obtained even though it is inaccurate. For example, an agronomist may apply fertilizer to certain key plots, knowing that they will provide more favorable yields than others. To protect against induced bias, advice of an individual trained in statistics should be sought in the design and someone else aware of search pitfalls should serve in an auditing capacity. 72 Error Error is defined as, “an act, assertion, or belief that unintentionally deviates from what is correct, right, or true”. In a business research process, there is sure to be some error in the results because there is the involvement of human intelligence and the use of sampling methods that may not be always accurate. The absolute value of the difference between an unbiased point estimate and the corresponding population parameter is known as a sampling error. It arises because the data is collected from a part, rather than the whole of the population. The sampling error can be more reliable by increasing the sample size. Total survey errors are of two types: Random sampling error & non-sampling error. Random Sampling Error Random sampling error or sampling error is the difference between the sample results and the results of a census conducted by identical procedures. Although a representative sample is taken, there is always a slight deviation between the true population value and the sample value. This is because the sample selected is not perfectly representative of the test population. Therefore, a small random sampling error is evident. As the sampling error is the outcome of chance, the laws of probabilities are applicable to it. The sampling error is inversely proportional to the sample size. As the sample size increases, the sampling error decreases. Although sampling errors cannot be avoided altogether, they can be controlled through careful sample designs, large samples, and multiple contacts to assure Fundamentals of Research Methodology 73 representative response. Random sampling error represents how accurately the sample’s true mean value(x sample), is representative of the population’s true mean value(X population). Non-Sampling error: (Measurement errors) Non- sampling errors also known as systematic errors occur due to the nature of the study’s design and the correctness of execution. Non-sampling error includes non-observation errors and measurement errors. The other main cause of unrepresentative samples is non sampling error. This type of error can occur whether a census or a sample is being used. Like sampling error, non sampling error may either be produced by participants in the statistical study or be an innocent by product of the sampling plans and procedures. Non- observational errors occur when data cannot be collected from the sampling unit or variable. Measurement errors arise from various sources like respondents, interviewers, supervisors, and even data processing systems. Non-observation error is further divided into non-coverage and non-response error. In probability sampling, each element of the population has a non-zero chance of selection into the sample. Non-coverage error occurs when an element in the target population has no chance of being selected into the sample. Non-response error occurs when data cannot be collected from the element actually selected into the sample. This may be due to the refusal of the element to cooperate because of language barrier, health limitation, or non availability of the element during the survey 74 period. Selection of faulty sampling frame may also result in a non- sampling error. Sampling frame error is said to occur when certain non potential respondents are included in the sampling frame and certain deserving respondents are rejected. The simplest example of non sampling error is inaccurate measurements due to malfunctioning instruments or poor procedures. For example, consider the observation of human weights. If persons are asked to state their own weights themselves, no two answers will be of equal reliability. The people will have weighed themselves on different scales in various states of poor calibration. An individual`s weight fluctuates diurnally by several pounds, so that the time of weighing will affect the answer. The scale reading will also vary with the person`s state of undress. Responses therefore will not be of comparable validity unless all persons are weighed under the same circumstances. Basic Concepts in Hypothesis Testing There are two types of statistical inferences: estimation of population parameters and hypothesis testing. Hypothesis testing is one of the most important tools of application of statistics to real life problems. Most often, decisions are required to be made concerning populations on the basis of sample information. Statistical tests are used in arriving at these decisions. Error When using probability to decide whether a statistical test provides evidence for or against our predictions, there is always a chance of Fundamentals of Research Methodology 75 driving the wrong conclusions. Even when choosing a probability level of 95%, there is always a 5% chance that one rejects the null hypothesis when it was actually correct. This is called Type I error, represented by the Greek letter . It is possible to err in the opposite way if one fails to reject the null hypothesis when it is, in fact, incorrect. This is called Type II error, represented by the Greek letter . These two errors are represented in the following chart. Null Hypothesis (H 0 ) is true He truly is not guilty Alternative Hypothesis (H 1 ) is true He truly is guilty Accept Null Hypothesis Acquittal Right decision Wrong decision Type II Error Reject Null Hypothesis Conviction Wrong decision Type I Error Right decision For example, if we reject Ho when it is false, we have made a correct decision (upper-right cell.) However, if we reject Ho when it is true, we have made a “Type I error” (upper left cell.) This error has a particular name, alpha, noted by the Greek character. In a correctly designed experiment, we make our decision to reject Ho based on a probability statement – how rare we would see the results under the assumption of the null hypothesis. If that probability turns out to be 76 small, say at 0.05, we conclude that this is sufficient evidence to reject innocence and proclaim guilt. On the other hand, if Ho is false (the person is indeed guilty) and do not reject Ho, we commit a Type II error. The probability of committing a Type II error is called beta. The power of the test is defined to be one minus beta. When a test has low power it means that we are likely to make a Type II error, (i.e., fail to reject Ho when it is actually false.) Looking at it the other way, the higher the “power” the better chance of rejecting Ho when it is false. Characteristics of Hypothesis A hypothesis may be defined as a logically conjectured relationship between two or more variables, expressed in the form of a testable statement. Relationship is proposed by using a strong logical argumentation. This logical relationship may be part of theoretical framework of the study. The following are some of the important factors should be considered while frame hypothesis 1. Hypothesis should be clear and specific 2. Hypothesis should be competent of being tested 3. Hypothesis should be limited in scope 4. Hypothesis should be state the variables relationship 5. Hypothesis should be consistent with known facts Fundamentals of Research Methodology 77 Let us look at some of the hypotheses 1. Employees in organization have higher than average level of satisfaction (variable). 2. Level of job satisfaction of the employees is associated with their level of efficiency. 3. Level of job satisfaction of the employees is positively associated with their level of efficiency. 4. The higher the level of job satisfaction of the employees the lower their level of absenteeism. These are testable propositions. First hypothesis contains only one variable. The second one has two variables which have been shown to be associated with each other but the nature of association has not been specified (non-directional relationship). In the third hypothesis we have gone a step further where in addition to the relationship between the two variables, the direction of relationship (positive) has also been given. In the fourth hypothesis level of efficiency has been replaced with level of absenteeism, the direction of relationship between the two variables has been specified (which is negative). In the following discussion the researcher will find these hypotheses being quoted as part of the examples. Types of Hypotheses i. Descriptive Hypothesis Descriptive hypothesis contains only one variable thereby it is also called as univariate hypothesis. Descriptive hypotheses typically state the existence, size, form, or distribution of some variable. The 78 first hypothesis contains only one variable. It only shows the distribution of the level of commitment among the officers of the organization which is higher than average. Such a hypothesis is an example of a Descriptive Hypothesis. Researchers usually use research questions rather than descriptive hypothesis. For example a question can be: What is the level of commitment of the officers in your organization? ii. Relational Hypothesis These are the propositions that describe a relationship between two variables. The relationship could be non-directional or directional, positive or negative, causal or simply correlational. While stating the relationship between the two variables, if the terms of positive, negative, more than, or less than are used then such hypotheses are directional because the direction of the relationship between the variables (positive/negative) has been indicated (see hypotheses 3 and 4). These hypotheses are relational as well as directional. The directional hypothesis is the one in which the direction of the relationship has been specified. Non-directional hypothesis is the one in which the direction of the association has not been specified. The relationship may be very strong but whether it is positive or negative has not been postulated (see hypothesis 2). Correlational hypotheses State merely that the variables occur together in some specified manner without implying that one causes the other. Such weak claims are often made when we believe that there are more basic Fundamentals of Research Methodology 79 causal forces that affect both variables. For example: Level of job satisfaction of the officers is positively associated with their level of efficiency. Here we do not make any claim that one variable causes the other to change. That will be possible only if we have control on all other factors that could influence our dependent variable. Explanatory (causal) hypotheses Imply the existence of, or a change in, one variable causes or leads to a change in the other variable. This brings in the notions of independent and the dependent variables. Cause means to “help make happen.” So the independent variable may not be the sole reason for the existence of, or change in the dependent variable. The researcher may have to identify the other possible causes, and control their effect in case the causal effect of independent variable has to be determined on the dependent variable. This may be possible in an experimental design of research. iii. Null Hypothesis It is used for testing the hypothesis formulated by the researcher. Researchers treat evidence that supports a hypothesis differently from the evidence that opposes it. They give negative evidence more importance than to the positive one. It is because the negative evidence tarnishes the hypothesis. It shows that the predictions made by the hypothesis are wrong. The null hypothesis simply states that there is no relationship between the variables or the relationship between the variables is “zero.” That is how symbolically null hypothesis is denoted as “H0”. For example: 80 H0 =There is no relationship between the level of satisfaction and the level of efficiency. Or H0 =The relationship between level of job satisfaction and the level of efficiency is zero. Or The two variables are independent of each other. It does not take into consideration the direction of association (i.e. H0 is non directional), which may be a second step in testing the hypothesis. First we look whether or not there is an association then we go for the direction of association and the strength of association. Experts recommend that we test our hypothesis indirectly by testing the null hypothesis. In case we have any credibility in our hypothesis then the research data should reject the null hypothesis. Rejection of the null hypothesis leads to the acceptance of the alternative hypothesis. iv. Alternative Hypothesis The alternative (to the null) hypothesis simply states that there is a relationship between the variables under study. In our example it could be: there is a relationship between the level of job satisfaction and the level of efficiency. Not only there is an association between the two variables under study but also the relationship is perfect which is indicated by the number “1”. Thereby the alternative hypothesis is symbolically denoted as “H1”. It can be written like this: Fundamentals of Research Methodology 81 H1: There is a relationship between the level of job satisfaction of the officers and their level of efficiency. v. Research Hypothesis Research hypothesis is the actual hypothesis formulated by the researcher which may also suggest the nature of relationship i.e. the direction of relationship. In our example it could be: Level of job satisfaction of the officers is positively associated with their level of efficiency. The Role of the Hypothesis In research, a hypothesis serves several important functions: 1. It guides the direction of the study: Quite frequently one comes across a situation when the researcher tries to collect all possible information on which he could lay his hands on. Later on he may find that only part of it he could utilize. Hence there was an unnecessary use of resources on trivial concerns. In such a situation, hypothesis limits what shall be studied and Hypothesis should be related to available techniques of research. Hypothesis may have empirical reality; still we are looking for tools and techniques that could be used for the collection of data. If the techniques are not there then the researcher is handicapped. Therefore, either the techniques are already available or the researcher is in a position to develop suitable techniques for the study. Hypothesis should be related to a body of theory. Hypothesis has to be supported by theoretical argumentation. For 82 this purpose the research may develop his/her theoretical framework which could help in the generation of relevant hypothesis. For the development of a framework the researcher shall depend on the existing body of knowledge. In such an effort a connection between the study in hand and the existing body of knowledge can be established. That is how the study could benefit from the existing knowledge and later on through testing the hypothesis could contribute to the reservoir of knowledge. 2. It identifies facts that are relevant and those that are not: Who shall be studied (married couples), in what context they shall be studied (their consumer decision making), and what shall be studied (their individual perceptions of their roles). 3. It suggests which form of research design is likely to be the most appropriate: Depending upon the type of hypothesis a decision is made about the relative appropriateness of different research designs for the study under consideration. The design could be a survey design, experimental design, content analysis, case study, participation observation study, and/or Focus Group Discussions. 4. It provides a framework for organizing the conclusions of the findings: Characteristics of a Testable Hypothesis Hypothesis must be conceptually clear. The concepts used in the hypothesis should be clearly defined, operationally if Fundamentals of Research Methodology 83 possible. Such definitions should be commonly accepted and easily communicable among the research scholars. Hypothesis should have empirical referents. The variables contained in the hypothesis should be empirical realities. In case these are not empirical realities then it will not be possible to make the observations. Being handicapped by the data collection, it may not be possible to test the hypothesis. Watch for words like ought, should, bad. Hypothesis must be specific. The hypothesis should not only be specific to a place and situation but also these should be narrowed down with respect to its operation. Let there be no global use of concepts whereby the researcher is using such a broad concept which may all inclusive and may not be able to tell anything. For example somebody may try to propose the relationship between urbanization and family size. Yes urbanization influences in declining the size of families. But urbanization is such comprehensive variable which hide the operation of so many other factor which emerge as part of the urbanization process. These factors could be the rise in education levels, women’s levels of education, women empowerment, emergence of dual earner families, decline in patriarchy, accessibility to health services, role of mass media, and could be more. Therefore the global use of the word ‘urbanization’ may not tell much. Hence it is suggested to that the hypothesis should be specific. 84 Steps in Hypothesis Testing Statisticians follow a formal process to determine whether to reject a null hypothesis, based on sample data. This process, called hypothesis testing, consists of five steps. Step-1- State the hypotheses. This involves stating the null and alternative hypotheses. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false. Step-2- Formulate an analysis plan. The analysis plan describes how to use sample data to evaluate the null hypothesis. The evaluation often focuses around a single test statistic. Step-3- Analyze sample data. Find the value of the test statistic (mean score, proportion, t-score, z-score, etc.) described in the analysis plan. Step-4- Interpret results. Apply the decision rule described in the analysis plan. Step- 5- Make a decision. If the test statistic falls in the critical region If the test statistic does not fall in the Critical region Reject H 0 in favour of H A . Conclude that there is not enough evidence to reject H 0 . Fundamentals of Research Methodology 85 Decision Rules The analysis plan includes decision rules for rejecting the null hypothesis. In practice, statisticians describe these decision rules in two ways - with reference to a P-value or with reference to a region of acceptance. P-value. The strength of evidence in support of a null hypothesis is measured by the P-value. Suppose the test statistic is equal to S. The P-value is the probability of observing a test statistic as extreme as S, assuming the null hypotheis is true. If the P-value is less than the significance level, we reject the null hypothesis. Region of acceptance. The region of acceptance is a range of values. If the test statistic falls within the region of acceptance, the null hypothesis is not rejected. The region of acceptance is defined so that the chance of making a Type I error is equal to the significance level. The set of values outside the region of acceptance is called the region of rejection. If the test statistic falls within the region of rejection, the null hypothesis is rejected. In such cases, we say that the hypothesis has been rejected at the α level of significance. These approaches are equivalent. Some statistics texts use the P- value approach; others use the region of acceptance approach. In subsequent lessons, this tutorial will present examples that illustrate each approach. 86 One-Tailed and Two-Tailed Tests A test of a statistical hypothesis, where the region of rejection is on only one side of the sampling distribution, is called a one-tailed test. For example, suppose the null hypothesis states that the mean is less than or equal to 10. The alternative hypothesis would be that the mean is greater than 10. The region of rejection would consist of a range of numbers located on the right side of sampling distribution; that is, a set of numbers greater than 10. A test of a statistical hypothesis, where the region of rejection is on both sides of the sampling distribution, is called a two-tailed test. For example, suppose the null hypothesis states that the mean is equal to 10. The alternative hypothesis would be that the mean is less than 10 or greater than 10. The region of rejection would consist of a range of numbers located on both sides of sampling distribution; that is, the region of rejection would consist partly of numbers that were less than 10 and partly of numbers that were greater than 10. Fundamentals of Research Methodology 87 Chapter - V Tools for Data Collection Mailed questionnaire Rating scale Checklist Document schedule/data sheet Schedule for institutions Construction of schedules and questionnaires The process of construction Data need determination Preparation of “Dummy” tables Determination of the respondents’ level Data gathering method decision Instrument drafting Evaluation of the draft instrument Pre-testing: Specification of procedures/instructions Designing the format Question Construction Question relevance and content Types of questions to be avoided 88 Types of surveys Selecting the survey method Population Issues Sampling issues Question issues Pilot studies and pre-tests Pre-test Meaning Need for Pre-testing Purposes of Pre-testing Advantages and disadvantages of various data collection techniques Fundamentals of Research Methodology 89 Chapter - V Tools for Data Collection The researcher would have to decide which sort of data he would be using (thus collecting) for his study and accordingly he will have to select one or the other method of data collection. The methods of collecting primary and secondary data differ since primary data are to be originally collected, while in case of secondary data the nature of data collection work is merely that of compilation. We describe the different methods of data collection, with the pros and cons of each method. The various methods of data gathering involve the use of appropriate recording forms. These are called tools or instruments of data collection. They consist of Observation schedule Interview guide Interview schedule Mailed questionnaire Rating scale Checklist Document schedule/data sheet Schedule for institutions Each of the above tools is used for a specific method of data gathering: Observation schedule for observation method, interview 90 schedule and interview guide for interviewing, questionnaire for mail survey, and so on. Functions The tools of data collection translate the research objectives into specific questions/ items, the responses to which will provide the data required to achieve the research objectives. In order to achieve this purpose, each question/item must convey to the respondent the idea or group of ideas required by the research objectives, and each item must obtain a response which can be analysed for fulfilling the research objectives. Information gathered through the tools provides descriptions of characteristics of individuals, institutions or other phenomena under study. It is useful for measuring the various variables pertaining to the study. The variables and their interrelationships are analysed for testing the hypothesis or for exploring the content areas set by the research objectives. A brief description of the various tools of data collection is given below. Observation schedule This is a form on which observations of an object or a phenomenon are recorded. The items to be observed are determined with reference to the nature and objectives of the study. They are grouped into appropriate categories and listed in the schedule in the order in which the observer would observe them. Fundamentals of Research Methodology 91 The schedule must be so devised as to provide the required verifiable and quantifiable data and to avoid selective bias and misinterpretation of observed items. The units of observation must be simple, and meticulously worded so as to facilitate precise and uniform recording. Interview guide Interviews Interviews are a far more personal form of research than questionnaires. In the personal interview, the interviewer works directly with the respondent. Unlike with mail surveys, the interviewer has the opportunity to probe or ask follow-up questions. And, interviews are generally easier for the respondent, especially if what is sought is opinions or impressions. Interviews can be very time consuming and they are resource intensive. The interviewer is considered a part of the measurement instrument and interviewers have to be well trained in how to respond to any contingency. Almost everyone is familiar with the telephone interview. Telephone interviews enable a researcher to gather information rapidly. Most of the major public opinion polls that are reported were based on telephone interviews. Like personal interviews, they allow for some personal contact between the interviewer and the respondent. And, they allow the interviewer to ask follow-up questions. But they also have some major disadvantages. Many people don't have publicly-listed telephone numbers. Some don't have telephones. People often don't like the intrusion of a call to their 92 homes. And, telephone interviews have to be relatively short or people will feel imposed upon. Interview schedule and mailed Questionnaire both these tools are widely used in surveys. Both are complete lists of questions on which information is elicited from the respondents. The basic difference between them lies in recording responses. While the interviewer fills out a schedule, the respondent completes a questionnaire. Rating Scale This is a recording form used for measuring individual's attitudes, aspirations and other psychological and behavioural aspects, and group behaviour. Checklist This is the simplest of all the devices. It consists of a prepared list of items pertinent to an object or a particular task. The presence or absence of each item may be indicated by checking 'yes' or 'no' or multipoint scale. The use of a checklist ensures a more complete consideration of all aspects of the object, act or task. Checklists contain terms, which the respondent understands, and which more briefly and succinctly express his views than answers to open-ended question. It is a crude device, but careful pre-test can make it less so. It is at best when used to test specific hypothesis. It may be used as an independent tool or as a part of a schedule/questionnaire. Fundamentals of Research Methodology 93 Document Schedule/Data Sheet This is a list of items of information to be obtained from documents, records and other materials. In order to secure measurable data, the items included in the schedule are limited to those that can be uniformly secured from a large number of case histories or other records. Schedule for Institutions This is used for survey of organisations like business enterprises, educational institutions, social or cultural organisations and the like. It will include various categories of data relating to their profile, functions and performance. These data are gathered from their records, annual reports and financial statements. Construction of Schedules and Questionnaires Schedule vs. Questionnaire Schedules and questionnaires are the most common instruments of data collection. These two types of tools have much in common. Both of them contain a set of questions logically related to a problem under study; both aim at eliciting responses from the respondents; in both cases the content, response structure, the wordings of questions, question sequence, etc. are the same for all respondents. Then why should they be denoted by the different terms: 'schedule' and 'questionnaires'? This is because the methods for which they are used are different. While a schedule is used as a tool for interviewing, a questionnaire is used for mailing. 94 This difference in usage gives rise to a subtle difference between these two recording forms. That is, the interviewer in a face-to-face interviewing fills a schedule, whereas the respondent himself fills in a questionnaire. Hence the need for using two different terms. The tool is referred to as a schedule when it is used for interviewing; and it is called a questionnaire when it is sent to a respondent for completion and return. The process of construction The process of construction of a schedule and a questionnaire is almost same, except some minor differences in mechanics. This process is not a matter of simply listing questions that comes to researchers mind. It is a rational process involving much time, effort and thought. It consists of the following major steps: Data need determination: As an interview schedule or a mailed questionnaire is an instrument for gathering data for a specific study, its construction should flow logically from the data required for the given study. Preparation of “Dummy” tables: The best way to ensure the requirements of information is to develop “dummy” tables in which to display the data to be gathered. Determination of the respondents’ level: Who are our respondents? Are they persons with specialized knowledge relating to the problem under study? Or are they lay people? What is their level of Fundamentals of Research Methodology 95 knowledge and understanding? The choice of words and concepts depends upon the level of the respondents' knowledge. Data gathering method decision: Which communication mode is most appropriate - face-to-face interview or mailing? The choice of question structure depends largely on the communication mode chosen. Instrument drafting: After determining the data required for the study, first, a broad outline of the instrument may be drafted, listing the various broad categories of data. Second, the sequence of these groupings must be decided. Third, the questions to be asked under each group heading must be listed. All conceivable items relevant to the 'data need' should be compiled. Evaluation of the draft instrument: In consultation with other qualified persons, the researcher must rigorously examine each question in the draft instrument. Pre-testing: The revised draft must be pre-tested in order to identify the weaknesses of the instrument and to make the required further revisions to rectify them. Specification of procedures/instructions: After the instruction is finalised after pre-tests, the procedures or instructions, relating to its use must be specified. Designing the format: The format should be suited to the needs of the research. The instrument should be divided into different sections relating to the different aspects of the problem. 96 Question Construction A survey instrument - interview schedules or questionnaire - is useful for collecting various types of information, viz., (a) factual information - facts about the respondents: sex, age, marital status, education, religion, caste or social class, income and occupation; and facts about events and circumstances, (b) psychological information such as attitudes, opinions, beliefs, and expectations, and (c) behavioural information, like social participation, and so on. Once the information need is determined as explained in the previous topic, we can begin question construction. This involves four major decision areas. They are: (a) question relevance and content, (b) question wording, (c) response form, and (d) question order or sequence. Question relevance and content Question to be included in the instrument should pass certain tests. Is it relevant to the research objectives? Can it yield significant information for answering an investigative question? If not, it should note be included in the instrument. Question wording This is a difficult task. The function of a question in a schedule/questionnaire is to elicit particular information without distortion. “Questioning people”, says opinion “is more like trying to catch a particular elusive fish, by hopefully casting different kinds of bait at different depths, without knowing what goes on beneath the Fundamentals of Research Methodology 97 surface.” As the meaning of words differs from person to person, the question designer should choose words which have the following characteristics: a. Shared vocabulary. b. Uniformity of meaning. c. Exactness. d. Simplicity. e. Neutrality. The words to be used must be neutral ones, i.e., free from the distorting influence of fear, prestige, bias or emotion. Certain other problem areas of question wording are a. Unwarranted assumptions, b. Personalization, c. Presumptions, d. Hypothetical question, e. Questions in embarrassing matters. Some of the approaches to deal with this problem are: i. to express the question in the third person; instead of asking the respondent for his views, he is asked about the views of others: ii. to use a drawing of two persons in a certain setting with 'balloons' containing speech coming from their mouths, as in a cartoon - leaving one person's balloon empty and asking the respondent to put himself in the position of that person and to fill in the missing words; and iii. to use sentence completion tests. 98 Response form or types of Questions The third major area in question construction is the types of questions to be included in the instrument. They may be classified into open questions and closed questions. Closed questions may be dichotomous, multiple choice or declarative ones. Types of questions to be avoided A good questionnaire forms an integrated whole. The researcher weaves questions together so they flow smoothly. He or she includes introductory remarks and instructions for clarification and measures each variable with one or more survey questions. What should be asked? The problem definition will indicate which type of information must be collected to answer the research question; different types of questions may be better at obtaining certain type of information than others. 1. Questionnaire Relevancy A questionnaire is relevant if no unnecessary information is collected and if the information that is needed to solve the problem is obtained. Asking the wrong or an irrelevant question is a pitfall to be avoided. If the task is to pinpoint compensation problems, for example, questions asking for general information about morale may be inappropriate. To ensure information relevancy, the researcher must Fundamentals of Research Methodology 99 be specific about data needs, and there should be a rationale for each item of information. 2. Questionnaire Accuracy Once the researcher has decided what should be asked, the criterion of accuracy becomes of primary concern. Accuracy means that the information is reliable and valid. While experienced researchers believe that one should use simple, understandable, unbiased, unambiguous, and nonirritating words. Obtaining accurate answer from respondents is strongly influenced by the researcher’s ability to design a questionnaire that facilitates recall and that will motivate the respondent to cooperate. Therefore avoid jargon, slang, and abbreviations. The respondents may not understand some basic terminology. Respondents can probably tell thee interviewer whether they are married, single, divorced, separated, or widowed, but providing their “marital status” may present a problem. Therefore, asking somebody about his/her marital status while the person may not understand the meaning of marital status is likely to mess up the information. Words used in the questionnaire should be readily understandable to all respondents. 3. Avoid Ambiguity, Confusion, and Vagueness. Ambiguity and vagueness plague most question writers. A researcher might make implicit assumptions without thinking of respondents’ perspectives. For example, the question, “what is your income?” could mean weekly, monthly, or annual: family or personal; before taxes or after taxes; for this year or last year; from salary or from all 100 sources. The confusion causes inconsistencies in how different respondents assign meaning to and answer the question. Another source of ambiguity is the use indefinite words or response categories. Consider the words such as often, occasionally, usually, regularly, frequently, many, good, fair, and poor. Each of these words has many meanings. For one person frequent reading of Time magazine may be reading six or seven issues a year; for another it may be two issues a year. The word fair has great variety of meanings; the same is true for many indefinite words. 4. Avoid Double-Barreled Questions Make each question about one and only one. A double barreled question consists of two or more questions joined together. It makes the respondent’s answer ambiguous. For example, if asked, “Does this company have pension and health insurance benefits?” a respondent at the company with health insurance benefits only might answer either yes or no. The response has an ambiguous meaning and the researcher cannot be certain of the respondent’s intentions. When multiple questions are asked in one question, the results may be exceedingly difficult to interpret. 5. Avoid Leading Questions Make respondents feel that all responses are legitimate. Do not let them aware of an answer that the researcher wants. A leading question is the one that leads the respondent to choose one response over another by its wording. For example, the question, “you don’t smoke, do you?” leads respondents to state that they do not smoke. Fundamentals of Research Methodology 101 “Don’t you think that women should be empowered?” In most the cases the respondent is likely to agree with the statement. 6. Avoid Loaded Questions Loaded questions suggest a socially desirable answer or are emotionally charged. “Should the city government repair all the broken streets?” Most of the people are going to agree with this question simply because this is highly socially desirable. A question which may be challenging the traditionally set patterns of behavior may be considered as emotionally charged i.e. it is loaded with such material which may hit the emotions of the people. Look at some behaviors associated with masculinity in Pakistani society. Let us ask a husband “Have you ever been beaten up by your wife?” Straight away this question may be considered to be a challenge to the masculinity of the person. Hence it may be embarrassing for the person to admit such an experience. Therefore, even if the husband was beaten up by his wife, he might give a socially desirable answer. 7. Avoid Burdensome Questions that may Tax the Respondent’s Memory A simple fact of human life is that people forget. Researchers writing questions about past behavior or events should recognize that certain questions may make serious demand on the respondent’s memory. “How did you feel about your brother when you were 6 years old?” It may very difficult to recall something from the childhood. 102 8. Arrange Questions in a Proper Sequence The order of question, or the question sequence, may serve several functions for the researcher. If the opening questions are interesting, simple to comprehend, and easy to answer, respondent’s cooperation and involvement can be maintained throughout the questionnaire. If respondent’s curiosity is not aroused at the outset, they can become disinterested and terminate the interview. Sequencing specific questions before asking about broader issues is a common cause of question order bias. In some situations it may be advisable to ask general question before specific question to obtain the freest opinion of the respondent. This procedure, known as funnel technique, allows the researcher to understand the respondent’s frame of reference before asking specific questions about the level of respondent’s information and intensity of his or her opinions. 9. Use Filter Question, if Needed Asking a question that doesn’t apply to the respondent or that the respondent is not qualified to answer may be irritating or may cause a biased response. Including filter question minimizes the chance of asking questions that are inapplicable. Filter question is that question which screens out respondents not qualified to answer a second question. For example the researcher wants to know about the bringing up of one’s children. “How much time do you spend playing games with your oldest child?” What if the respondent is unmarried? Even if the respondent is married but does not have the child. In both these situations the question is inapplicable to him/her. Fundamentals of Research Methodology 103 Before this question the person may put a filter question whether or not the respondent is married. 10. Layout of the questionnaire There are two format or layout issues: the overall physical layout of the questionnaire and the format of questions and responses. Good lay out and physical attractiveness is crucial in mail, Internet, and other self-administered questionnaires. For different reason it is also important to have a good layout in questionnaires designed for personal and telephone interviews. Give each question a number and put identifying information on questionnaire. Never cramp questions together or create a confusing appearance. Make a cover sheet or face sheet for each, for administrative use. Put the time and date of the interview, the interviewer, the respondent identification number, and interviewer’s comments and observations on it. Give interviewers and respondents instructions on the questionnaire. Print instructions in a different style from question to distinguish them. Lay out is important for mail questionnaires because there is no friendly interviewer to interact with the respondent. Instead the questionnaire’s appearance persuades the respondents. In mail surveys, include a polite, professional cover letter on letterhead stationery, identifying the researcher and offering a telephone number for any questions. Always end with “Thank you for your participation.” 104 Question order or Sequence The order in which questions are arranged in a schedule/ questionnaire is as important as question wording. It has two major implications. First, an appropriate sequence can ease the respondent's task in answering. Second, the sequence can either create or avoid biases due to context effects, i.e., the effects of preceding questions on the response to later questions. Mechanics of the Schedule and Questionnaire In addition to question wording and question construction, the mechanics of the form should also be considered in the design of a schedule/questionnaire. The mechanics of the form has several aspects: items of the form, instruction, pre-coding, sectionalisation, spacing, paper, printing, margins, etc. Items of the form: The following items are mandatory for schedules and questionnaires. 1. The name of the organization collecting the data should appear at the top of front -page. The name of the sponsor, of the study, if any should also be shown. 2. The title of the study should appear in large print next to the name of the organization on the first page. Below this title, the title of the tool - e.g., 'Schedule for-consumers; - may be noted. . 3. The confidentialness of the data should be made cleat. 4. A place for writing the date of filling in the form should be provided. 5. A serial number to each copy of the tool may be assigned. 6. The pages of the instrument should be numbered. Fundamentals of Research Methodology 105 Instructions: In the face sheet below the title of the questionnaire, a brief statement of the objective of the study, the confidentialness of the data, and instructions relating to answering the questions may be provided. . Pre-coding: Items in the tool should be pre-coded so as to facilitate transcription of data. Sectionalisation: There should be a separate section for each topical area. Spacing: For each open-ended question, an adequate space should be provided for answer. There should, indeed more space than seems necessary, for some interviewers/ respondents may write in a large script for legibility. Moreover, liberal spacing is a stimulus for the questionnaire respondent to write more fully. Even short-answer questions should be spaced, so that the interviewer/respondent will not easily confuse the line, from which he is reading. Paper: The paper used for mimeographing/printing should be of good quality. Printing: Mailed questionnaire should necessarily be printed in order to make it attractive and to minimise the postal expenditure. Margins: One inch margin on the left side of the sheet and one-half inch margin on other sides may be provided. If the instrument is to be bound, left-side margin should conform to the type of binding used. 106 Indentation: This is required for 'yes' or 'no' questions. If the respondent's answer is 'yes', then a series of questions is offered. If the answer is 'no' a different series of questions is offered. Note of thanks: A final note or comment of thanks for the cooperation of the respondent should be included at the end of the instrument. Types of Surveys Surveys can be divided into two broad categories: the questionnaire and the interview. Questionnaires are usually paper-and-pencil instruments that the respondent completes. Interviews are completed by the interviewer based on the respondent says. Sometimes, it's hard to tell the difference between a questionnaire and an interview. For instance, some people think that questionnaires always ask short closed-ended questions while interviews always ask broad open- ended ones. But you will see questionnaires with open-ended questions (although they do tend to be shorter than in interviews) and there will often be a series of closed-ended questions asked in an interview. Survey research has changed dramatically in the last ten years. We have automated telephone surveys that use random dialing methods. There are computerized kiosks in public places that allow people to ask for input. A whole new variation of group interview has evolved as focus group methodology. We'll discuss the relative advantages and disadvantages of these different survey types in Advantages and Disadvantages of Survey Methods. Fundamentals of Research Methodology 107 Mail survey There are many advantages to mail surveys. 1. They are relatively inexpensive to administer. 2. It can send the exact same instrument to a wide number of people. 3. They allow the respondent to fill it out at their own convenience. But there are some disadvantages as well. 1. Response rates from mail surveys are often very low. And, 2. Mail questionnaires are not the best vehicles for asking for detailed written responses. A second type is the group administered questionnaire. A sample of respondents is brought together and asked to respond to a structured sequence of questions. Traditionally, questionnaires were administered in group settings for convenience. The researcher could give the questionnaire to those who were present and be fairly sure that there would be a high response rate. If the respondents were unclear about the meaning of a question they could ask for clarification. And, there were often organizational settings where it was relatively easy to assemble the group (in a company or business, for instance). What's the difference between a group administered questionnaire and a group interview or focus group? In the group administered questionnaire, each respondent is handed an instrument and asked to complete it while in the room. Each respondent completes an instrument. In the group interview or focus 108 group, the interviewer facilitates the session. People work as a group, listening to each other's comments and answering the questions. Someone takes notes for the entire group -- people don't complete an interview individually. A less familiar type of questionnaire is the household drop-off survey. In this approach, a researcher goes to the respondent's home or business and hands the respondent the instrument. In some cases, the respondent is asked to mail it back or the interview returns to pick it up. This approach attempts to blend the advantages of the mail survey and the group administered questionnaire. Like the mail survey, the respondent can work on the instrument in private, when it's convenient. Like the group administered questionnaire, the interviewer makes personal contact with the respondent they don't just send an impersonal survey instrument. And, the respondent can ask questions about the study and get clarification on what is to be done. Generally, this would be expected to increase the percent of people who are willing to respond. Selecting the Survey Method Selecting the type of survey going to use is one of the most critical decisions in many social research contexts. The researcher has to use your judgment to balance the advantages and disadvantages of different survey types. Here, number of questions might ask that can help guide decision about selecting type of survey. Fundamentals of Research Methodology 109 Population Issues The first set of considerations has to do with the population and its accessibility. Can the population be enumerated? For some populations, a complete listing of the units that will be sampled. For others, such a list is difficult or impossible to compile. For instance, there are complete listings of registered voters or person with active drivers’ licenses. But no one keeps a complete list of homeless people. If doing a study that requires input from homeless persons, you are very likely going to need to go and find the respondents personally. In such contexts, you can pretty much rule out the idea of mail surveys or telephone interviews. Is the population literate? Questionnaires require that your respondents can read. While this might seem initially like a reasonable assumption for many adult populations, we know from recent research that the instance of adult illiteracy is alarmingly high. And, even if your respondents can read to some degree, your questionnaire may contain difficult or technical vocabulary. Clearly, there are some populations that you would expect to be illiterate. Young children would not be good targets for questionnaires. Are there language issues? We live in a multilingual world. Virtually every society has members who speak other than the predominant language. Some countries 110 (like Canada) are officially multilingual. And, our increasingly global economy requires us to do research that spans countries and language groups. Can you produce multiple versions of your questionnaire? For mail instruments, can you know in advance the language your respondent speaks, or do you send multiple translations of your instrument? Can you be confident that important connotations in your instrument are not culturally specific? Could some of the important nuances get lost in the process of translating your questions? Will the population cooperate? People who do research on immigration issues have a difficult methodological problem. They often need to speak with undocumented immigrants or people who may be able to identify others who are. Why would we expect those respondents to cooperate? Although the researcher may mean no harm, the respondents are at considerable risk legally if information they divulge should get into the hand of the authorities. The same can be said for any target group that is engaging in illegal or unpopular activities. What are the geographic restrictions? Is your population of interest dispersed over too broad a geographic range for you to study feasibly with a personal interview? It may be possible for you to send a mail instrument to a nationwide sample. You may be able to conduct phone interviews with them. But it will almost certainly be less feasible to do research that requires Fundamentals of Research Methodology 111 interviewers to visit directly with respondents if they are widely dispersed. Sampling Issues The sample is the actual group you will have to contact in some way. There are several important sampling issues you need to consider when doing survey research. What data is available? What information do you have about your sample? Do you know their current addresses? Their current phone numbers? Are your contact lists up to date? Can respondents be found? Can your respondents be located? Some people are very busy. Some travel a lot. Some work the night shift. Even if you have an accurate phone or address, you may not be able to locate or make contact with your sample. Who is the respondent? Who is the respondent in your study? Let's say you draw a sample of households in a small city. A household is not a respondent. Do you want to interview a specific individual? Do you want to talk only to the "head of household" (and how is that person defined)? Are you willing to talk to any member of the household? Do you state that you will speak to the first adult member of the household who opens the door? What if that person is unwilling to be interviewed but 112 someone else in the house is willing? How do you deal with multi- family households? Similar problems arise when you sample groups, agencies, or companies. Can you survey any member of the organization? Or, do you only want to speak to the Director of Human Resources? What if the person you would like to interview is unwilling or unable to participate? Do you use another member of the organization? Can all members of population be sampled? If you have an incomplete list of the population (i.e., sampling frame) you may not be able to sample every member of the population. Lists of various groups are extremely hard to keep up to date. People move or change their names. Even though they are on your sampling frame listing, you may not be able to get to them. And, it's possible they are not even on the list. Are response rates likely to be a problem? Even if you are able to solve all of the other population and sampling problems, you still have to deal with the issue of response rates. Some members of your sample will simply refuse to respond. Others have the best of intentions, but can't seem to find the time to send in your questionnaire by the due date. Still others misplace the instrument or forget about the appointment for an interview. Low response rates are among the most difficult of problems in survey research. They can ruin an otherwise well-designed survey effort. Fundamentals of Research Methodology 113 Question Issues Sometimes the nature of what you want to ask respondents will determine the type of survey you select. What types of questions can be asked? Are you going to be asking personal questions? Are you going to need to get lots of detail in the responses? Can you anticipate the most frequent or important types of responses and develop reasonable closed-ended questions? How complex will the questions be? Sometimes you are dealing with a complex subject or topic. The questions you want to ask are going to have multiple parts. You may need to branch to sub-questions. Will screening questions be needed? A screening question may be needed to determine whether the respondent is qualified to answer your question of interest. For instance, you wouldn't want to ask someone their opinions about a specific computer program without first "screening" them to find out whether they have any experience using the program. Sometimes you have to screen on several variables (e.g., age, gender, experience). The more complicated the screening, the less likely it is that you can rely on paper-and-pencil instruments without confusing the respondent. 114 Can question sequence be controlled? Is your survey one where you can construct in advance a reasonable sequence of questions? Or, are you doing an initial exploratory study where you may need to ask lots of follow-up questions that you can't easily anticipate? Will lengthy questions be asked? If your subject matter is complicated, you may need to give the respondent some detailed background for a question. Can you reasonably expect your respondent to sit still long enough in a phone interview to ask your question? Will long response scales be used? If you are asking people about the different computer equipment they use, you may have to have a lengthy response list (CD-ROM drive, floppy drive, mouse, touch pad, modem, network connection, external speakers, etc.). Clearly, it may be difficult to ask about each of these in a short phone interview. Pilot Studies and Pre-Tests Pilot Study The need for Pilot Study It is difficult to plan a major study or project without adequate knowledge of its subject matter, the population it is to cover, their level of knowledge and understanding and the like. What are the issues involved? What are the concepts associated with the subject matter? How can they be operationalised? What method of study is Fundamentals of Research Methodology 115 appropriate? How long the study will take? How much money it will cost? These and other related questions call for a good deal of knowledge of the subject matter of the study and its dimensions. In order to gain such pre-knowledge of the subject matter of an extensive study, a preliminary investigation is con-ducted. This is called a pilot study. Pre-test Meaning While a pilot study is a full-fledged miniature study of a problem, pre-test is a trial test of a specific aspect of the study such as method of data collection or data collection instrument - interview schedule, mailed questionnaire or measurement scale. Need for Pre-testing An instrument of data collection is designed with reference to the data requirements of the study. But it cannot be perfected purely on the basis of a critical scrutiny by the designer and other researchers. It should he empirically tested. As emphatically pointed by Goode and Hatt, “no amount of thinking, no matter how logical the mind or brilliant the insight, is likely to take the place of careful empirical checking”. Hence pre-testing of a draft instrument is indispensable. Pre-testing-means trial administration of the instrument to a sample of respondents before finalising it. 116 Purposes of Pre-testing Pre-testing has several purposes: (1) to test whether the instrument would elicit responses required to achieve the research objectives, (2) to test whether the content of the instrument is relevant and adequate, (3) to test whether wording of questions is clear and suited to the understanding of the respondents, (4) to test the other qualitative aspects of the instrument like question structure and question sequence, and (5) to develop appropriate procedure for administering the instrument with reference to field conditions. Fundamentals of Research Methodology 117 Advantages and disadvantages of various data collection techniques 118 Fundamentals of Research Methodology 119 Chapter - VI Data Processing Editing Field Editing In-House Editing Editing for Consistency Editing for Completeness Item Non-response Editing Questions Answered out of Order Coding Code Construction Production Coding Data Entries Cleaning Data Data Transformation Indexes and Scales Unidimensionality Index Construction Weighting Scoring and Score Index 120 Chapter - VI Data Processing Once the data begins to flow in, attention turns to data analysis. If the project has been done correctly, the analysis planning is already done. Back at the research design stage or at least by the completion of the proposal or the pilot test, decisions should have been made about how to analyze the data. During the analysis stage several interrelated procedures are performed to summarize and rearrange the data. The goal of most research is to provide information. There is a difference between raw data and information. Information refers to a body of facts that are in a format suitable for decision making, whereas data are simply recorded measures of certain phenomenon. The raw data collected in the field must be transformed into information that will answer the sponsor’s (e.g. manager’s) questions. The conversion of raw data into information requires that the data be edited and coded so that the data may be transferred to a computer or other data storage medium. If the database is large, there are many advantages to utilizing a computer. Assuming a large database, entering the data into computer follows the coding procedure. Editing Information may have been noted in haste and now required to be deciphered. Data should be edited before being presented as Fundamentals of Research Methodology 121 information to ensure that figures or words are accurate. Editing can be done manually or with computer or both depending upon the medium, whether paper or electronic. Editing is the process of checking and adjusting the data for omissions, legibility, and consistency. Editing may be differentiated from coding, which is the assignment of numerical scales or classifying symbols to previously edited data. The purpose of editing is to ensure the completeness, consistency, and readability of the data to be transferred to data storage. The editor’s task is to check for errors and omissions on the questionnaires or other data collection forms. The editor may have to reconstruct some data. For instance, a respondent may indicate weekly income rather than monthly income, as requested on the questionnaire. The editor must convert the information to monthly data without adding any extraneous information. The editor “should bring to light all hidden values and extract all possible information from a questionnaire, while adding nothing extraneous.” The editing is done on two levels- micro and macro. In micro- editing, the basic records are corrected. Usually, all records are securitized one by one for apparent mistakes. The intent is to determine consistency of the data. For example, at one place the distances may be in miles while in another place these may be in km. Or there may be obvious mistake like showing a distance of 100 km where it should be only 10 km or less. 122 On macro level, aggregates are compared with data from other surveys or files or earlier versions of the same data. This is done to determine compatibility. For example, one survey has estimated total number of residents in a sector at 2,000. In another survey of family size, the total number of residents workout to be 2,500. Obviously, one of the estimates is wrong. In case, the figure of 2,000 was considered correct because of the double-check, the second would have to be reviewed for mistakes in totaling or multiplication. Several types of data edits are available. In validity edits, it is ensured that specified units of measures (like kgs, liters or sq. Meters) are written. In range edit, one would observe that the values are within pre-established or common sense limits. Similarly, there are edits for duplications, consistency and history. On the other hand, there are data errors such as (i) unasked questions, (ii) unrecorded answers and (iii) inappropriate responses. Sometimes, a researcher is confronted with a exceptional but true figure like a very unusual temperature of 90 F (34.4 C). This is “unrepresentative” or “outlying” observations in a data set. What should we do about the “outliers” in a sample? “Should such data be deleted?” is for the researcher to decide. Occasionally, a fieldworker makes a mistake and records an improbable answer (e.g., birth year: 1843) or interviews an ineligible Fundamentals of Research Methodology 123 respondent (e.g., someone too young to qualify). Seemingly contradictory answers, such as “no” to automobile ownership but “yes” to an expenditure on automobile insurance, may appear on a questionnaire. There are many problems like these that must be dealt with before the data can be coded. Editing procedures are conducted to make the data ready for coding and transfer to data storage. Field Editing In large projects, field supervisors are often responsible for conducting preliminary field edits. The purpose of field editing the same day as the interview is to catch technical omissions (such as a blank page), check legibility of the handwriting, and clarify responses that are logically or conceptually inconsistent. If a daily field editing is conducted, a supervisor who edits completed questionnaires will frequently be able to question the interviewers, who may be able to recall the interview well enough to correct any problems. The number of “no answers,” or incomplete answers can be reduced with a rapid follow-up simulated by a field edit. The daily edit also allows fieldworkers to re-contact the respondent to fill in omissions before the situation has changed. The field edit may also indicate the need for further training of interviewers. In-House Editing Although almost simultaneous editing in the field is highly desirable, in many situations (particularly with mail questionnaires), early 124 reviewing of the data is not possible. In-house editing rigorously investigates the results of data collection. Editing for Consistency: The in-house editor’s task is to ensure that inconsistent or contradictory responses are adjusted and that answers will not be a problem for coders and keyboard punchers. Consider the situation in which a telephone interviewer has been instructed to interview only registered voters that requires voters to be 18 years old. If the editor’s reviews of a questionnaire indicate that the respondent was only 17 years of age, the editor’s task is to eliminate this obviously incorrect sampling unit. Thus, in this example, the editor’s job is to make sure that thee sampling unit is consistent with thee objectives of the study. Editing requires checking for logically consistent responses. The in- house editor must determine if the answers given by a respondent to one question are consistent with those given to other, related questions. Many surveys utilize filter questions or skip questions that direct the sequence of questions, depending upon respondent’s answer. In some cases the respondent will have answered a sequence of questions that should not have been asked. The editor should adjust these answers, usually to “no answer’ or “inapplicable,” so that the responses will be consistent. Editing for Completeness: In some cases the respondent may have answered only the second portion of a two-part question. An in- house editor may have to adjust the answers to the following Fundamentals of Research Methodology 125 question for completeness. Does your organization have more than one Internet Web site? Yes ____ No. _____ If a respondent checked neither “yes” nor “No”, but indicated three Internet Web sites, the editor may check the “yes” to ensure that this answer is not missing from the questionnaire. Item Non-response: It is a technical term for an unanswered question on an otherwise complete questionnaire. Specific decision rules for handling this problem should be meticulously outlined in the editorial instructions. In many situations the decision rule will be to do nothing with the unanswered question: the editor merely indicates in item non response by writing a message instructing the coder to record a “missing value” or blank as the response. However, in case the response is necessary then the editor uses the plug value. The decision rule may to “plug in” an average or neutral value in each case of missing data. A blank response in an interval scale item with a midpoint would be to assign the midpoint in the scale as the response to that particular item. Another way is to assign to the item the mean value of the responses of all those who have responded to that particular item. Another choice is to give the item the mean of the responses of this particular respondent to all other questions measuring the variables. Another decision rule may be to alternate the choice of the response categories used as plug values (e.g. “yes” the first time, “no” the second time, “yes” the third time, and so on). The editor must also decide whether or not an entire questionnaire is 126 “usable.” When a questionnaire has too many (say 25%) answers missing, it may not be suitable for the planned data analysis. In such a situation the editor simply records the fact that a particular incomplete questionnaire has been dropped from the sample. Editing Questions Answered out of Order: Another situation an editor may face is thee need to rearrange the answers to an open- ended response to a question. For example, a respondent may have provided the answer to a subsequent question in his answer to an earlier open-ended response question. Because the respondent had already clearly identified his answer, the interviewer may have avoided asking the subsequent question. The interviewer may have wanted to avoid hearing “I have already answered that earlier” and to maintain rapport with the respondent and therefore skipped the question. To make the response appear in the same order as on other questionnaires, the editor may remove the out-of-order answer to the section related to the skipped question. Coding Coding is a “systematic way in which to condense extensive data sets into smaller analyzable units through the creation of categories and concepts derived from the data.” It is the “process by which verbal data are converted into variables and categories of variables using numbers, so that the data can be entered into computers for analysis.” Fundamentals of Research Methodology 127 Coding involves assigning numbers or other symbols to answers so the responses can be grouped into limited number of classes or categories. The classifying of data into limited categories sacrifices some data detail but is necessary for efficient analysis. Nevertheless, it is recommended that try to keep the data in raw form so far it is possible. When the data have been entered into the computer you can always ask the computer to group and regroup the categories. In case the data have been entered in the compute in grouped form, it will not be possible to disaggregate it. Although codes are generally considered to be numerical symbols, they are more broadly defined as the rules for interpreting, classifying, and recording data. Codes allow data to be processed in a computer. Researchers organize data into fields, records, and files. A field is a collection of characters (a character is a single number, letter of the alphabet, or special symbol such as the question mark) that represent a single type of data. A record is collection of related fields. A file is a collection of related records. File, records, and fields are stored on magnetic tapes, floppy disks, or hard drives. Researchers use a coding procedure and codebook. A coding procedure is a set of rules stating that certain numbers are assigned to variable attributes. For example, a researchers codes males as 1 and females as 2. Each category of variable and missing information needs a code. A codebook is a document (i.e. one or more pages) describing the coding procedure and the location of data for variables in a format that computers can use. When you code data, it is very important to create a well- 128 organized, detailed codebook and make multiple copies of it. If you do not write down the details of the coding procedure, or if you misplace thee codebook, you have lost the key to the data and may have to recode the data again. Researchers begin thinking about a coding procedure and a codebook before they collect data. For example a survey researcher pre-codes a questionnaire before collecting thee data. Pre-coding means placing the code categories (e.g. 1 for male, 2 for female) on the questionnaire. Sometimes to reduce dependence on codebooks, researchers also place the location in the computer format on the questionnaire. If the researcher does not pre-code, his or her first step after collecting and editing of data is to create a codebook. He or she also gives each case an identification number to keep track of the cases. Next, the researcher transfers the information from each questionnaire into a format that computers can read. Code Construction When the question has a fixed-alternative (closed ended) format, the number of categories requiring codes is determined during the questionnaire design stage. The codes 8 and 9 are conventionally given to “don’t know” (DK) and “no answer” (NA) respectively. However, many computer program fields recognize a blank field or a certain character symbol, such as a period (.), as indicating a missing value (no answer). There are two basic rules for code construction. First, the coding categories should be exhaustive – that is, coding Fundamentals of Research Methodology 129 categories should be provided for all subjects or objects or responses. With a categorical variable such as sex, making categories exhaustive is not a problem. However, when the response represents a small number of subjects or when the responses might be categorized in a class not typically found, there may be a problem. Second, the coding categories should also be mutually exclusive and independent. This means that there should be no overlap between the categories, to ensure that a subject or response can be placed in only one category. This frequently requires that an “other” code category be included, so that the categories are all inclusive and mutually exclusive. For example, managerial span of control might be coded 1, 2, 3, 4, and “5 or more.” The “5 or more” category ensures everyone a place in a category. When a questionnaire is highly structured, pre-coding of the categories typically occurs before the data are collected. In many cases, such as when researchers are using open-ended response questions, a framework for classifying responses to questions cannot be established before data collection. This situation requires some careful thought concerning the determination of categories after editing process has been completed. This is called post-coding or simply coding. The purpose of coding open-ended response questions is to reduce the large number of individual responses to a few general categories of answers that can be assigned numerical scores. Code construction in these situations necessarily must reflect the judgment of the 130 researcher. A major objective in code-building process is to accurately transfer the meaning from written answers to numeric codes. Production Coding Transferring the data from the questionnaire or data collection form after the data have been collected is called production coding. Depending upon the nature of the data collection form, codes may be written directly on the instrument or on a special coding sheet. Data Entries Use of scanner sheets for data collection may facilitate the entry of the responses directly into the computer without manual keying in the data. In studies involving highly structured paper questionnaires, an Optical scanning systemmay be used to read material directly to the computer’s memory into the computer’s memory. Optical scanners process the marked-sensed questionnaires and store thee answers in a file. Cleaning Data The final stage in the coding process is the error checking and verification, or “data cleaning” stage, which is a check to make sure that all codes are legitimate. Accuracy is extremely important when coding data. Errors made when coding or entering data into a computer threaten the validity of measures and cause misleading results. A researcher who has perfect sample, perfect measures, and Fundamentals of Research Methodology 131 no errors in gathering data, but who makes errors in the coding process or in entering data into a computer, can ruin a whole research project. DATA TRANSFROMATION Data transformation is the process of changing data from their original form to a format that is more suitable to perform a data analysis that will achieve the research objectives. Researchers often modify the values of a scalar data or create new variables. For example many researchers believe that response bias will be less if interviewers ask consumers for their year of birth rather than their age, even though the objective of the data analysis is to investigate respondents’ age in years. This does not present a problem for thee research analyst, because a simple data transformation is possible. The raw data coded at birth year can be easily transformed to age by subtracting the birth year from the current year. Collapsing or combining categories of a variable is a common data transformation that reduces the number of categories. For example five categories of Likert scale response categories to a question may be combined like: the “strongly agree” and the “agree” response categories are combined. The “strongly disagree” and the “disagree” response categories are combined into a single category. The result is the collapsing of the five-category scale down to three. Creating new variables by re-specifying the data numeric or logical transformations is another important data transformation. For 132 example, Likert summated scale reflect the combination of scores (raw data) from various attitudinal statements. The summative score for an attitude scale with three statements is calculated as follows: Summative Score = Variable 1 + Variable 2 + Variable 3 This calculation can be accomplished by using simple arithmetic or by programming a computer with a data transformation equation that creates the new variable “summative score.” The researchers have created numerous different scales and indexes to measure social phenomenon. For example scales and indexes have been developed to measure the degree of formalization in bureaucratic organization, the prestige of occupations, the adjustment of people in marriage, the intensity of group interaction, the level of social activity in a community, and the level of socio-economic development of a nation. Keep it in mind that every social phenomenon can be measured. Some constructs can be measured directly and produce precise numerical values (e.g. family income). Other constructs require the use of surrogates or proxies that indirectly measure a variable (e.g. job satisfaction). Second, a lot can be learned from measures used by other researchers. We are fortunate to have the work of thousands of researchers to draw on. It is not always necessary to start from a scratch. We can use a past scale or index, or we can modify it for our own purposes. The process of creating measures for a construct evolves over time. Measurement is an ongoing process with constant change; new Fundamentals of Research Methodology 133 concepts are developed, theoretical definitions are refined, and scales or indexes that measure old or new constructs are improved. Technology had made life easy. Data can be collected on scanner answer sheet which enable a researcher to enter them directly into computer file. In other cases, raw data would be manually entered into computer as data file. Here some software like SPSS data editor can be used to enter, edit and view the contents. It is easy to add, change or delete values after the data has been entered. Indexes and Scales Scales and indexes are often used interchangeably. One researcher’s scale is another’s index. Both produce ordinal- or interval- level measures of variable. To add to the confusion, scale and index techniques can be combined in one measure. Scales and indexes give a researcher more information about variables and make it possible to assess the quality of measurement. Scales and indexes increase reliability and validity, and they aid in data reduction; that is condense and simplify the information that is collected. A scale is a measure in which the researcher captures the intensity, direction, level, or potency of a variable construct. It arranges responses or observation on a continuum. A scale can use single indicator or multiple indicators. Most are at thee ordinal level of measurement. 134 An index is a measure in which a researcher adds or combines several distinct indicators of a construct into a single score. This composite score is often a simple sum of multiple indicators. It is used for content or convergent validity. Indexes are often measured at the interval or ratio level. Researchers sometimes combine the features of scales and indexes in a single measure. This is common when a researcher has several indicators that are scales. He or she then adds these indicators together to yield a single score, thereby an index. Unidimensionality: It means that al the items in a scale or index fit together, or measure a single construct. Unidimensionality says: If you combine several specific pieces of information into a single score or measure, have all the pieces measure the same thing. (each sub dimension is part of the construct’s overall content). For example, we define the construct “feminist ideology” as a general ideology about gender. Feminist ideology is a highly abstract and general construct. It includes a specific beliefs and attitudes towards social, economic, political, family, sexual relations. The ideology’s five belief areas parts of a single general construct. The parts are mutually reinforcing and together form a system of beliefs about dignity, strength, and power of women. Fundamentals of Research Methodology 135 Index Construction You may have heard about a consumer price index (CPI). The CPI, which is a measure of inflation, is created by totaling the cost of buying a list of goods and services (e.g. food, rent, and utilities) and comparing the total to the cost of buying the same list in the previous year. An index is combination of items into a single numerical score. Various components or subgroups of a construct are each measured, and then combined into one measure. There are many types of indexes. For example, if you take an exam with 25 questions, the total number of questions correct is a kind of index. It is a composite measure in which each question measures a small piece of knowledge, and all the questions scored correct or incorrect are totaled to produce a single measure. One way to demonstrate that indexes are not a very complicated is to use one. Answer yes or no to the seven questions that follow on the characteristics of an occupation. Base your answers on your thoughts regarding the following four occupations: long-distance truck driver, medical doctor, accountant, telephone operator. Score each answer 1 for yes and 0 for no. 1. Does it pay good salary? 2. Is the job secure from layoffs or unemployment? 3. Is the work interesting and challenging? 4. Are its working conditions (e.g. hours, safety, time on the road) good? 136 5. Are there opportunities for career advancement and promotion? 6. Is it prestigious or looked up to by others? 7. Does it permit self-direction and thee freedom to make decisions? Total the seven answers for each of the four occupations. Which had the highest and which had the lowest score? The seven questions are our operational definition of the construct good occupation. Each question represents a subpart of our theoretical definition. Creating indexes is so easy that it is important to be careful that every item in the index has face validity. Items without face validity should be excluded. Each part of the construct should be measured with at least one indicator. Of course, it is better to measure the parts of a construct with multiple indicators. Another example of an index is college quality index. Our theoretical definition says that a high quality college has six distinguished characteristics: (1) fewer students per faculty member, (2) a highly educated faculty, (3) more books in the library, (4) fewer students dropping out of college, (5) more students who go to advanced degrees, and (6) faculty members who publish books or scholarly articles. We score 100 colleges on each item, and then add the score for each to create an index score of college quality that can be used to compare colleges. Indexes can be combined with one another. For example, in order to strengthen the college quality index. We add a sub-index on teaching quality. The index contain eight elements: (1) average size of classes, (2) percentage of class time devoted to discussion, (3) number of Fundamentals of Research Methodology 137 different classes each faculty member teaches, (4) availability of faculty to students outside the classroom, (5) currency and amount of reading assigned, (6) degree to which assignments promote learning, (7) degree to which faculty get to know each student, and (8) student ratings of instruction. Similar sub-index measures can be created for other parts of the college quality index. They can be combined into a more global measure of college quality. This further elaborates the definition of a construct “quality of college.” Weighting An important issue in index construction is whether to weight items. Unless it is otherwise stated, assume that an index is un-weighted. Likewise, unless we have a good reason for assigning different weights, use equal weights. A weighted index gives each item equal weight. It involves adding up the items without modification, as if each were multiplied by 1 (or – 1 for negative items that are negative). Scoring and Score Index In one our previous discussions we had tried to measure job satisfaction. It was operationalized with the help of dimensions and elements. We had constructed number of statements on each element with 5 response categories using Likert scale i.e. strongly agree, agree, undecided, disagree, and strongly disagree. We could score each of these items from 1 to 5 depending upon the degree of agreement with the statement. The statements have been both 138 positive as well as negative. For positive statements we can score straight away from 5 to 1 i.e. strongly agree to strongly disagree. For the negative statements we have to reverse the score i.e. 1 for “strongly agree,” 2 for “agree,” 3 for “undecided” to 4 for “disagree,” and 5 for “strongly disagree.” Reason being that negative multiplied by a negative becomes positive i.e. a negative statement and a person strongly disagreeing with it implies that he or she has a positive responsive so we give a score of 5 in this example. In our example, let us say there were 23 statements measuring for different elements and dimensions measuring job satisfaction. When on each statement the respondent could get a minimum score of 1 and a maximum score of 5, on 23 statements a respondent could get a minimum score of (23 X 1) and a maximum score of (23 X 5) 115. In this way the score index ranges from 23 to 115, the lower end of the score index showing minimum job satisfaction and upper end as the highest job satisfaction. In reality we may not find any on the extremes, rather the respondents could be spread along this continuum. We could use the raw scores of independent and dependent variable and apply appropriate statistics for testing the hypothesis. We could also divide the score index into different categories like high “job satisfaction” and “low satisfaction” for presentation in a table. We cross-classify job satisfaction with some other variable, apply appropriate statistics for testing the hypothesis. Fundamentals of Research Methodology 139 Chapter-VII Report Writing Types of Report Writing Research Report Writing Business Report Writing Science Report Writing Different Steps in Report Writing: Logical analysis of subject matter. Preparation of final outline. Preparation of Rough Draft. Rewriting and Polishing. Preparation of final Bibliography. Writing the final draft. Mechanics of Report Writing Title Page Dedication Acknowledgements Table of Contents Lists of Illustrations Elements of research report 140 Chapter-VII Report Writing A report is a dreadfully official document that is written to serve the range of purpose in the engineering and business disciplines; sciences and social sciences. Therefore, they need to be clear-cut and accurate. Good report writing call for--- professionalism, profound knowledge of the subject, attentiveness, and outstanding writing proficiency. Types of Report Writing --- Research Report Writing Business Report Writing Science Report Writing Research Report Writing--- To presents the tangible proof of the conducted research is the major intention of the academic assignment. When writing on research report, you must ponder over clarity, organization, and content. Research reports are all the more same to technical reports, lab reports, formal reports and scientific papers which comprise a quite consistent format that will facilitate to put information noticeably, making it crystal clear. Business Report Writing--- In business milieu, Business report writing happens to be an indispensable part of the communication process. Executive summary is written in a non-technical manner. By and large, audience for business reports will consist of upper level Fundamentals of Research Methodology 141 manager, for that reason we should take the audience needs in consideration. Go on with the introduction to articulate the problem and determine the scope of the research. To attain the desired results, don't fail to state about the precise quantitative tools. Science Report Writing--- Parallel to a business report, science report writing also corresponds with the line of investigation. To report upon an empirical investigation, these reports make use of standard scientific report format, portraying technique, fallout and conclusions. As an assignment in undergraduate papers within the scientific disciplines, it is required frequently. The main objective of the Science report is to boast an aim, the technique which enlightens how the project has been analyzed, the outcomes which presents the findings and the conclusion. This embraces advance research suggestions and your own biased opinion on the topic which has been talked about. When writing a science report, do not fail to remember to use heading and subheadings in order to direct a reader through your work. In the form of tables and graphs, Statistical evidence should be incorporated in appendices. Than refer to it in the body of scientific report. Research Report is the major component of the research study. Report writing is the important stage in the research activity. The hypothesis of the study, the objective of the study and the data collection and data analysis can be well presented in report. This 142 report writing will help others to understand the findings of the research. Report writing is integral part of research and hence it cannot be isolated. Report writing is not a mechanical process but it is an art. It requires skill. Guidelines on how to prepare a professional-style research report are not routinely available to the researchers. For this reason, the following information on report writing with a suggested format is provided to be helpful to researchers. Different Steps in Report Writing It is the critical stage and hence it requires patience. These is no mechanical formulate to present a report, though there are certain steps to be followed while writing a research report. The usual steps in report writing can be indicated in the following manner: Logical analysis of subject matter. Preparation of final outline. Preparation of Rough Draft. Rewriting and Polishing. Preparation of final Bibliography. Writing the final draft. It is pertinent to follow these steps and hence it is essential to understand these steps thoroughly. Fundamentals of Research Methodology 143 (a) Logical analysis of subject matter When a researcher thinks of doing a research, he must select subject and topic of his research work. The subject must be of his own interest and there must be scope for further research. Such can be selected and developed logically or chronologically. He must find out mental connections and associations by way of analysis to finalize his subject. Logical treatment often consists in developing from the simple possible to the most complex strictures. He can use the deductive method or inductive method in his research work. Secondly the alternative in selecting research subject is to use chronological method. In this method, he should concentrate on the connection or sequence in time or occurrence. The directions for doing or making something usually follow the chronological method. (b) Preparation of final outline Outlines are the framework upon which long written works are constructed. It is an aid to logical organization of the material and remainder of the points to be stressed in the report. He should rely on review of literature. The earlier research works can provide basic information as well as thinking to the researcher to pursue his subject. (c) Preparation of rough draft This follows the logical analysis of the subject and the preparation of the final outline. Such a step is of utmost importance for the researcher now sits to write down what he has done in the context of 144 his research study. Taking into account this purpose of research, the research report writing has its own significance. The researcher has already collected primary data and secondary data. He has also set his objectives of the study. Taking into account the objectives his study, he should make an attempt to prepare a draft report on the basis of analysis of the data. He should prepare a procedure to be followed in report writing. He must mention the limitations of his study. He may analyze data systematically with the help of statistical methods to arrive at the conclusions. The research is fact finding study which may lead the researcher to point out suggestions or recommendations. All the facts of value are to be brought together. In addition, accuracy of the facts incorporated into the text becomes necessary. For writing the rough draft the researcher should have control over his notes and should think continuously over the problem. There are three purpose in writing the rough draft, viz., to weave the material together for making clear connection, to assure the investigator himself of a satisfactory organisation and fullness of the facts, and to avoid blank paper fight that may be present in every researcher. Considerable trimming or editing have to be tone to make the research precise, concise and brief. (d) Rewriting and polishing the rough draft Research is a continuous process. Researcher must consider the data, write down his findings, reconsider them, and rewrite. This careful revision makes the difference between mediocre and good lice of writing. The researcher must concentrate on weakness in the logical development or presentation. He should check the consistency in his Fundamentals of Research Methodology 145 presentation. He must be aware that his report writing must be of definite pattern. He must also take utmost care of the language of writing a report. The purpose of the report is to convey to the interested persons the whole result of the study in sufficient detail and so arranged as to enable each reader to comprehend the data an so determine for himself the validity of conclusions. While drafting the second draft the researcher should concentrate largely on form of the research report and language used in the report. (e) Bibliography This helps the researcher to collect secondary source of the data. This is also useful to review the earlier research work. He should prepare the bibliography from the beginning of his research work. While selecting a topic or subject of research, he must refer books, journals, research projects and enlist the important documents in systematic manner. The bibliography must be in proper form. The researcher must have separate cards, indicating following details, readily available with him, so that he can make a note of it while he refers to a book/journal/research report. The bibliography must be included in the appendix of his research report. It must be exhaustive to cover all types of works the researcher has used. It must be arranged alphabetically. He can divide it in different sections, such as books in first section, journals in second, research reports in third etc. Generally the prescribed form for preparation of bibliography is as given below: 146 The book must be noted in following manner: 1. Name of Author (Surname first). 2. Title of book. 3. Publisher’s name, place and data of publication. 4. Number of volumes. The article can be mentioned in following manner: 1. Name of author (surname first) 2. Title of article (in quotation mark) 3. Name of periodical (underline it) 4. The volume or volume and number 5. Data of issue 6. The pagination (f) Final Report The final report must be written in a concise and objective style and in simple language. The researcher should avoid expressions in his report, such as “it seems”, “there may be” and like ones. He should avoid abstract terminology and technical jargon. He may refer to usual and common experiences to illustrate his point. The report writing is an art. No two researchers may have common style of report writing. But it must be interesting for a common man to add to his knowledge. A good research report depends not only upon the amount of the reading or notes taken or upon the form of presentation but also the accurate and through recording of the investigation. Fundamentals of Research Methodology 147 Following are some of the important principles for writing a good research report. 1. Make small sentences 2. Use simple words 3. Use familiar words 4. Avoid unnecessary words 5. Write to express not to impress 6. Use active verbs puts life into report writing 7. Always write research report with a particular reader in mind 8. Make the report short and sweet 9. Remember that every report should be an attempt to solve some intellectual problem Lay Out of Research Report There is scientific method for the layout of the research report. The layout of the report means as to what the research report should contain. The contents of the research report are noted below. The researcher must keep in mind that his research report must contain following aspects: (A) Preliminary Page (B) Main text 1. Introduction 2. Purpose of study 3. Significance of his study or statement of the problem 4. Review of literature 148 5. Methodology 6. Analysis and Interpretation of data 7. Conclusions and suggestions (C) End mater 1. Bibliography 2. Appendices These can be discussed in detail as under: (A) Preliminary Pages These must be title of the research topic and data. It should be followed by certificate, declaration. There must be preface of foreword to the research work followed by table of contents; the list of Exhibits so that the users of research report can easily locate the required information in the report. (B) Main Text It provides the complete outline of research report along with all details. The title page is reported in the main text. Details of text are given continuously as divided in different chapters. Each main section of the report should begin on an new page. (1)Introduction Its purpose is to introduce the research topic to readers. It must cover statement of the problem, hypotheses, objectives of study, review of literature, and the methodology to cover primary and secondary data, limitations of study and chapter scheme. Some may give in brief in Fundamentals of Research Methodology 149 the first chapter the introduction of the research project highlighting the importance of study. This is followed by research methodology in separate chapter. The methodology should point out the method of study, the research design and method of data collection. (2) Purpose of study This is crux of his research. It highlights main theme of his study. It must be in nontechnical language. It should be in simple manner so ordinary reader may follow it. The social research must be made available to common man. The research in agricultural problems must be easy for farmers to read it. The researcher must use review of literature or the data from secondary source for explaining the statement of the problems. (3) Significance of study Research is re-search and hence the researcher may highlight the earlier research in new manner or establish new theory. He must refer earlier research work and distinguish his own research from earlier work. He must explain how his research is different and how his research topic is different and how his research topic is important. In a statement of his problem, he must be able to explain in brief the historical account of the topic and way in which he can make and attempt. 150 (4) Review of Literature Research is a continuous process. He cannot avoid earlier research work. He must start with earlier work. He should note down all such research work, published in books, journals or unpublished thesis. He will get guidelines for his research from taking a review of literature. He should collect information in respect of earlier research work. A literature review is an appraising description of information found in the literature associated to chosen area of research. The literature review illustrates, summarize, appraise and clarify the literature for which are writing literature reviews. It should give a hypothetical foundation for the research and helps establish the nature of research. Unrelated works are removed completely while the marginal ones are considered critically. The importance of literature review cannot be denied because it is a review of writing on a subject. The under- mentioned reasons the importance of literature review: Literature review helps to find new ways to figure out any ambiguity or flaws in earlier researches. a. A literature review portrays the link of each work to the others. b. Literature review resolves any contradictory findings, or gaps in previous studies. c. Most importantly, literature review leads the way forward for further research. d. It adds the understanding and knowledge of the particular field. Fundamentals of Research Methodology 151 Factors should be consider while collect reviews 1. The literature review discovers the areas of controversy in the literature. 2. The literature review explains how each work is similar to and how it varies from the others. 3. Literature review should be well-structured around and directly linked to the research question you are developing. 4. The literature review should present an overview of the subject, issue or theory under consideration, along with the objectives of the literature review. Stages in Development Of Literature Review A literature review involves the four stages to advance: Problem Formulation First of all, the component issues of topic of literature review to examine or research are determined. Literature Search Finding materials are collected relevant to the subject being explored to write the literature review. Data Appraisal It is determined that which literature makes a worth mentioning contribution to the understanding of the topic of literature review. 152 Analysis Finally, the findings of relevant literature are analyzed to conclude and include in literature review. Tips to write a good literature review Need to keep entire and exact records and references of what you read and find during research. i. Learn the required citation style. ii. Make notes or summaries of the articles, books journals, papers whatever you read. iii. Researcher must infer and read between the lines when go through any written work. iv. Divide the literature review into different thematic parts which will help to focus. v. Read the leading published material and search for the current issues for the latest information. (5) Methodology It is related to collection of data. There are two sources for collecting data; primary and secondary. Primary data is original and collected in field work, either through questionnaire interviews. The secondary data relied on library work. Such primary data are collected by sampling method. The procedure for selecting the sample must be mentioned. The methodology must give various aspects of the problem that are studied for valid generalization about the Fundamentals of Research Methodology 153 phenomena. The scales of measurement must be explained along with different concepts used in the study. While conducting a research based on field work, the procedural things like definition of universe, preparation of source list must be given. We use case study method, historical research etc. He must make it clear as to which method is used in his research work. When questionnaire is prepared, a copy of it must be given in appendix. (6) Analysis and Interpretation of data Data so collected should be presented in systematic manner and with its help, conclusions can be drawn. This helps to test the hypothesis. Data analysis must be made to confirm the objectives of the study. Mainly the data collected from primary source need to be interpreted in systematic manner. The tabulation must be completed to draw conclusions. All the questions are not useful for report writing. One has to select them or club them according to hypothesis or objectives of study. (7) Conclusions/suggestions Data analysis forms the crux of the problem. The information collected in field work is useful to draw conclusions of study. In relation with the objectives of study the analysis of data may lead the researcher to pin point his suggestions. This is the most important part of study. The conclusions must be based on logical and statistical reasoning. The report should contain not only the generalization of inference but also the basis on which the inferences 154 are drawn. All sorts of proofs, numerical and logical, must be given in support of any theory that has been advanced. The primary data may lead to establish the results. He must have separate chapter on conclusions and recommendations. The conclusions must be based on data analysis. The conclusions must be such which may lead to generalization and its applicability in similar circumstances. (C) End Matter It covers relevant appendices covering general information, Questionnaire, Annual reports and the concepts and bibliography. The index may also be added to the report. (1) Bibliography The list of references must be arranged in alphabetical order and be presented in appendix. The books should be given in first section and articles are in second section and research projects in the third. The pattern of bibliography is considered convenient and satisfactory from the point of view of reader. Book with one author Author’s last name, first name. Title of the book. City: Publisher, Date of Publication. Example: J ones, Edward. The Toy. New York: Random House, 1987. Fundamentals of Research Methodology 155 Book with two authors Author’s last name, first name, and second author’s full name. Title of the book. Place of publication: Publisher, date of publication. Example: Edward and Amelia Smith. Strangers. New Delhi: Random House, 1987. Book without an author Title of the book. City: Publisher, Date of Publication. Example: Old Lake. New Delhi: Random House, 1987. Article in a book without an author Name of the article. Title of the book. City: Publisher, Date of Publication. Example: Agarwal.L.N, Personnel Management, New Delhi: Excel Books. (1998). Book with an editor Editor’s last name, first name, ed. Title of the book. Place of publication: Publisher, date of publication. J ones, Edward. 100 Recipes for You. New York: Random House, 1987. Short story or chapter of a book Author’s last name, first name. “Title.” Title of the book that the source comes from. Editor (ed.) of the book’s full name. Place of publication: Publisher, date of publication. Pages of the source. 156 Example: Kundu, Amitabh. “Learning to communicate.” The Toy. Ed. Helen Stevenson. New York: Random House, 1987. Encyclopedia article with an author/a signed article Author’s last name, first name. “Title”. Encyclopedia Title. Volume Number. Place of publication: Publisher, date of publication. Example: Charmes, J acques. “The Wild Swans.” World Book Encyclopedia. Volume 13. New York: Random House, 1987. Encyclopedia article without an author/an unsigned article “Title”. Encyclopedia Title. Volume number. Place of publication: Publisher, date of publication. Example: “The Wild Swans.” World Book Encyclopedia. Volume 13. New York: Random House, 1987. Journal article Author’s last name, first name “Article Title.” Name of magazine volume number: issue number (year of publication): page numbers. Example: Asha C.B “J ob satisfaction among women in relation to their family environment” Journal of Community Guidance And Research, Vol.11, No.1, (1994) pp.43-50. Case of multiple authorship If there are more than two authors or editors, then in the documentation the name of only the first is given and the multiple authorship is indicated by “et.al.” or ‘and other” Fundamentals of Research Methodology 157 Magazine article Author’s last name, first name. “Article title.” Magazine title date of publication: page numbers. Example: Banarjee, “Morginalisation”, Social Scientist, 1985, Vol.13, pp. 48-71. Newspaper article Author’s last name, first name. “Article title.” Newspaper title [city of publication, if not in title] date of publication, edition if necessary: section if necessary: page numbers. Example: Gunasekaran, “Low cost houses for Hosiery workers, the need of the house” The Hindu, 29 th September 2007, : 12 World Wide Web URL (Uniform Resource Locator or WWW address). Author (or item’s name, if mentioned), date. Example: (Boston Globe’s www address) http://www.boston.com. Today’s News, May 23, 2011. Interview Full name (last name first). Occupation. Date of interview. Example: Balakrishanan . Finance Manager. February 10, 2011. 158 (2) Appendices The general information in tabular form which is not directly used in the analysis of data but which is useful to understand the background of study can be given in appendix. Mechanics of Report Writing Title Page The title page is required. Please see sample page for correct placement and spacing. The title page should include: 1) a full title (the use of title case is recommended); 2) identification of document type(project, dissertation or Thesis); 3) the statement Presented in Partial Fulfillment of the Requirements for the Degree (insert the applicable degree such as Doctor of Philosophy, Master of philosophy, Master of Arts, Master of Science, etc.) in the University; 4) name of the candidate; 5) initials of previous earned degrees; 6) Name of the research guide with designation 7)Name of the college or university and 8) year of submission Dedication. A dedication is optional. If used, the dedication must be brief and centered on the page. See sample pages. Acknowledgements Like the dedication, acknowledgements are optional, but it is strongly suggested that students include them. Either spelling of the word, acknowledgements or acknowledgments, is acceptable. The acknowledgement is a record of the author’s indebtedness and Fundamentals of Research Methodology 159 includes notice of permission to use previously copyrighted materials that appear extensively in the text. The heading Acknowledgement (title case preferred) is centered without punctuation two inches from the top of the page. Table of Contents A table of contents is required. The heading Table of Contents (title case preferred) appears without punctuation centered two inches from the top of the page. The listing of contents begins at the left margin four spaces below the heading. The titles of all parts, sections, chapter numbers, and chapters are listed and must be worded exactly as they appear in the body of the document. The table of contents must include any appendices and their titles, if applicable. Use leader dots between the listed items and their page numbers. Lists of Illustrations Lists of illustrations are required if the document contains illustrations. The headings List of Tables, List of Figures, or other appropriate illustration designations (title case preferred) appears centered without punctuation two inches from the top of the page. The listing begins at the left margin four spaces below the heading. Illustrations should be identified by the same numbers and captions in their respective lists as they have been assigned in the document itself. 160 Margins. Top, right, and bottom margins should be set at one inch; the left margin should be at least 1.5 inches. Any pages with major headings, such as document title, chapter/major section titles, preliminary page divisions, abstract, appendices, and references at the end of the document should be set with a 1.5-inch left margin and a two-inch top margin. Font. The selected font should be 10 to 12 point and readable. The font should be consistent throughout the document. Captions, endnotes, footnotes, and long quotations may be slightly smaller than text font, if readable. Spacing. Double spacing is preferred, but 1.5 inch spacing is acceptable for long documents. Single spacing is recommended for bibliography entries, long quotations, long endnotes or footnotes, and long captions. Double spacing between each bibliography entry is recommended. Titles. Each major division of the document, including appendices, must have a title, Titles must be centered and have a two-inch top margin. The use of title case is recommended. If chapters are being used, they should be numbered and titled. For example: Chapter 1: Introduction. Page Numbers. Every page must have a page number except the title page and the copyright page. If a frontispiece (usually an illustration or quotation relevant to the subject) is included before the title page, it is neither counted nor numbered. Small Roman numerals Fundamentals of Research Methodology 161 (ii, iii, iv, etc.) are used for the preliminary pages: abstract, dedication, acknowledgments, vita, table of contents, and the lists of illustrations, symbols, abbreviations, and/or nomenclature. Page numbering begins with ii, which is the number assigned to the abstract. Arabic numerals are used for the remainder of the document, including the text and the reference material. The pages are numbered consecutively beginning with 1 and continue through the end of the document. The page numbers are centered at the bottom center of the page above the one inch margin. Note: You may need to set the footer margin to one inch and the body bottom margin to 1.3 or 1.5 inches to place the page number accurately. Notation. Notation practices differ widely among publications in the sciences, the humanities, and the social sciences. Candidates should confer with their advisors regarding accepted practice in their individual disciplines. That advice should be coupled with careful reference to appropriate general style manuals. 1. Arabic numerals should be used to indicate a note in the text. 2. Notes may be numbered in one of two ways: either consecutively throughout the entire manuscript or consecutively within each chapter. 3. Notes can be placed at the bottom of the page (footnotes) or at the end of a chapter or document (endnotes). Once chosen, the notation style must be consistent throughout the document. 162 4. Notes about information within tables should be placed directly below the table to which they apply, not at the bottom of the page along with notes to the text. Illustrations (tables, figures, charts, graphs, photos, etc.). See sample pages. Some documents include several types of illustrations. In such cases, it is necessary that each type of illustration (table, figure, chart, etc.) be identified with a different numbering series (Table 1, Table 2, and so on, or Chart 1, Chart 2, and so on). For each series, include a list with captions and page numbers in the preliminary pages (for example, List of Tables, List of Charts, etc.). These lists must be identified with major headings that are centered and placed at the two-inch margin. If an illustration is too large to fit on one page, you must indicate below the illustration on the lower right corner that it is continued. For example, the phrase continued is placed under the illustration, on the right hand side. On the following pages, include the illustration type, number, and the word continued above it at the left margin; for example, Map 2: Continued. If landscape orientation is used, the page number goes at the bottom of the page (portrait), not at the bottom of the illustration. Always stay in the margins. Most research reports include the following elements 1. Title page 2. Letter of transmittal 3. Table of contents 4. List of tables Fundamentals of Research Methodology 163 5. List of graphs 6. List of appendices 7. List of exhibits 8. Executive summary a. Major findings b. Conclusions c. Recommendations 9. Introduction i. Background to the problem ii. Statement of the problem 10. Approach to the problem 11. Research design a. Type of research design b. Information needs c. Data collection from secondary sources d. Data collection from primary sources e. Scaling techniques f. Questionnaire development and pretesting g. Sampling techniques h. Field work 12. Data analysis a. Methodology b. Plan of data analysis 13. Results 164 14. Limitations and caveats 15. Conclusions and recommendations 16. Appendix a. Questionnaires and forms b. Statistical output c. Lists Fundamentals of Research Methodology 165 Appendix 166 Multiple Choice Questions 1. Personal interviews conducted in shopping malls are known as: a. Mall interviews b. Mall intercept interviews c. Brief interviews d. None of the given options 2. WATS lines provided by long distance telephone service at fixed rates. In this regard, WATS is the abbreviation of: a. West Africa Theological Seminary b. Washtenaw Area Transportation Study c. Wide Area Telecommunications Service d. World Air Transport Statistics 3. A list of questions which is handed over to the respondent, who reads the questions and records the answers himself is known as the: a. Interview schedule b. Questionnaire c. Interview guide d. All of the given options 4. One of the most critical stages in the survey research process is: a. Research design b. Questionnaire design c. Interview design d. Survey design Fundamentals of Research Methodology 167 5. Question that consists of two or more questions joined together is called a: a. Double barreled question b. General question c. Accurate question d. Confusing question 6. The number of questionnaires returned or completed divided by the total number of eligible people who were contacted or asked to participate in the survey is called the: a. Response rate b. Participation rate c. Inflation rate d. None of the given options 7. To obtain the freest opinion of the respondent, when we ask general question before a specific question then this procedure is called as the: a. Research technique b. Qualitative technique c. Funnel technique d. Quantitative technique 8. A small scale trial run of a particular component is known as: a. Pilot testing b. Pre-testing c. Lab experiments d. Both A & B 168 9. Field testing of the questionnaire shows that: a. Respondents are willing to co-operate b. Respondents are not willing to co-operate c. Respondents do not like any participation d. All of the given options 10. Service evaluation of hotels and restaurants can be done by the: a. Self-administered questionnaires b. Office assistant c. Manager d. None of the given options 11. Which one of the following sets is the measure of central tendency? a. Mean, standard deviation, mode b. Mean, median, standard deviation c. Arithmetic mean, median, mode d. Standard deviation, internal validity, mode 12. In lab experiment the effect of Variables is controlled to evaluate the causal relationship. a. Extraneous b. Moderate c. Intervening d. All of the above Fundamentals of Research Methodology 169 13. Internal validity refers to . a. Researcher’s degree of confidence. b. Generalizability c. Operationalization d. All of the above 14. Which of the following is the weakest experimental design? a. One group pretest-posttest design b. Quasi- experimental design c. Two group posttest only design d. Ex post facto design 15. How many times the students appear in the research class is the example of _________. a. Intensity b. Space c. Frequency d. Direction 16. Disadvantage of content analysis is _ a. Researcher can increase the sample size b. Provides access on the subjects to which researcher does have physical access. c. Sometime documents provide incomplete account to the researcher d. Spontaneous feelings can be recorded when they occurred 170 17. Time consumed in mall intercept interview is_______ a. High b. Moderate c. Low d. Nil 18. “Teacher should create a friendly environment in the classroom” this is the type of a. Leading question b. Loaded question c. Double Barreled d. Burdensome question 19. Departmental stores selected to test a new merchandising display system is the example of a. Quota sampling b. Convenience sampling c. Judgmental sampling d. Purposive sampling 20. Discrete variable is also called………. a. zategorical variable b. Discontinuous variable c. Both A & B d. None of the above Fundamentals of Research Methodology 171 21. Which one of the following is not a characteristic of scientific method? a. Deterministic b. Rationalism c. Empirical d. Abstraction 22. The theoretical framework discusses the interrelationships among the………. a. Variables b. Hypothesis c. Concept d. Theory 23. Personal interviews conducted in shopping malls are known as__________ a. Mall interviews b. Mall intercept interviews c. Brief interviews d. None of the given options 24. _______is used to obtain the freest opinion of the respondent, by asking general question before a specific question. a. Research technique b. Qualitative technique c. Funnel technique d. Quantitative technique 172 25. In________ the interviewer and members jointly control the pace and direction of the interview. a. Field interview b. Telephonic interview c. Both A and B d. None of the given options 26. Randomization of test units is a part of _____________ a. Pretest b. Posttest c. Matching d. Experiment 27. Hypothesis refers to a. The outcome of an experiment b. A conclusion drawn from an experiment c. A form of bias in which the subject tries to outguess the experimenter d. A tentative statement about the relationship 38. A literature review requires a. Planning b. Good & clear writing c. Lot of rewriting d. All of the above Fundamentals of Research Methodology 173 29. A literature review is based on the assumption that a. Copy from the work of others b. Knowledge accumulates and learns from the work of others c. Knowledge disaccumulates d. None of the above option 30. A theoretical framework a. Elaborates the r/s among the variables b. Explains the logic underlying these r/s c. Describes the nature and direction of the r/s d. All of the above 31. Which of the following statement is not true? a. A research proposal is a document that presents a plan for a project b. A research proposal shows that the researcher is capable of successfully conducting the proposed research project c. A research proposal is an unorganized and unplanned project d. A research proposal is just like a research report and written before the research project 32. Preliminary data collection is a part of the a. Descriptive research b. Exploratory research c. Applied research d. Explanatory research 174 33. Conducting surveys is the most common method of generating a. Primary data b. Secondary data c. Qualitative data d. None of the above 34. After identifying the important variables and establishing the logical reasoning in theoretical framework, the next step in the research process is a. To conduct surveys b. To generate the hypothesis c. To focus group discussions d. To use experiments in an investigation 35. The appropriate analytical technique is determined by a. The research design b. Nature of the data collected c. Nature of the hypothesis d. Both A & B 36. The process of marking segments of data with symbols, descriptive words, or category names is known as a. Concurring b. Coding c. Coloring d. Segmenting Fundamentals of Research Methodology 175 37. What is the cyclical process of collecting and analyzing data during a single research study called? a. Interim analysis b. Inter analysis c. Inter-item analysis d. Constant analysis 38. What is the recording of reflective notes about what you are learning from your data during data analysis called? a. Coding b. Segmenting c. Memoing d. Reflecting 39. Which of the following is not one of Spradley’s types of relationships? a. Strict inclusion b. Sequence c. Cause-effect d. Correlational 40. Codes that apply to a complete document or case are called a. Cover codes b. False sheet codes c. c. Factual codes d. Factsheets codes 176 41. A classification system generally used in the social sciences that breaks something down into different types or levels is called a a. Diagram b. Flow chart c. Hierarchical category system d. Category 42. Codes developed before examining the current data being coded are called_____ a. Co-occuring codes b. Inductive codes c. A priori codes d. Facesheet codes 43. The process of quantifying data is referred to as ________ a. Typology b. Diagramming c. Enumeration d. Coding 44. Which of the following refers to the cyclical process of collecting and analyzing data during a single research study? a. Memoing b. Segmenting c. Coding c. Interim analysis d. Interim analysis Fundamentals of Research Methodology 177 45. Which research paradigm is based on the pragmatic view of reality? a. quantitative research b. qualitative research c. mixed research d. none of the above 46. Which research paradigm is least concerned about generalizing its findings? a. quantitative research b. qualitative research c. mixed research d. none of the above 47. Which of the following best describes quantitative research? a. the collection of nonnumerical data b. an attempt to confirm the researcher’s hypotheses c. research that is exploratory d. research that attempts to generate a new theory 48. A condition or characteristic that can take on different values or categories is called a. a constant b. a variable c. a cause-and-effect relationship d. a descriptive relationship 178 49. A variable that is presumed to cause a change in another variable is called a(n): a. categorical variable b. dependent variable c. independent variable d. intervening variable 50. All of the following are common characteristics of experimental research except: a. it relies primarily on the collection of numerical data b. it can produce important knowledge about cause and effect c. it uses the deductive scientific method d. it rarely is conducted in a controlled setting or environment 51. Which type of research provides the strongest evidence about the existence of cause- and-effect relationships? a. nonexperimental Research b. experimental Research 52. What is the key defining characteristic of experimental research? a. extraneous variables are never present b. a positive correlation usually exists c. a negative correlation usually exists d. manipulation of the independent variable Fundamentals of Research Methodology 179 53. In, random assignment to groups is never possible and the researcher cannot manipulate the independent variable. a. basic research b. quantitative research c. experimental research d. causal-comparative and correlational research 54. A positive correlation is present when a. Two variables move in opposite directions. b. Two variables move in the same direction. c. One variable goes up and one goes down d. Several variables never change 55. Research in which the researcher uses the qualitative paradigm for one phase and the quantitative paradigm for another phase is known as a. action research b. basic research c. quantitative research d. mixed method research e. mixed model research 56. Research that is done to understand an event from the past is known as ? a. experimental research b. historical research c. replication d. archival research 180 57. Which of the following includes examples of quantitative variables? a. age, temperature, income, height b. grade point average, anxiety level, reading performance c. gender, religion, ethnic group d. both a and b 58. What is the opposite of a variable? a. a constant b. an extraneous variable c. a dependent variable d. a data set 59. Which of the following is the type of non-experimental research in which the primary independent variable of interest is categorical? a. causal-comparative research b. experimental research c. qualitative research d. mixed research 60. Which of the following can best be described as a categorical variable? a. age b. annual income c. grade point average d. religion Fundamentals of Research Methodology 181 61. In research, something that does not "vary" is called a a. variable b. method c. constant c. control group 62. When interpreting a correlation coefficient expressing the relationship between two variables, it is very important to avoid a. checking the strength of relationship b. jumping to the conclusion of causality c. checking the direction of the relationship d. expressing a relationship with a correlation coefficient 63. The strongest evidence for causality comes from which of the following research methods? a. Experimental b. Causal-comparative c. Correlational d. Ethnography 64. Which correlation is the strongest? a. +.10 b. -.95 c. +.90 d. -1.00 182 65. The correlation between intelligence test scores and grades is: a. Positive b. Negative c. Perfect d. They are not correlated 66. A statement of the quantitative research question should: a. Extend the statement of purpose by specifying exactly the question(s) the researcher will address b. Help the research in selecting appropriate participants, research methods, measures, and materials c. Specify the variables of interest d. All of the above 67. Research hypotheses are ______ a. Formulated prior to a review of the literature b. Statements of predicted relationships between variables c. Stated such that they can be confirmed or refuted d. b and c 68. Hypotheses in qualitative research studies usually _____ a. Are very specific and stated prior to beginning the study b. Are often generated as the data are collected, interpreted, and analyzed c. Are never used d. Are always stated after the research study has been completed Fundamentals of Research Methodology 183 69. A research plan _____. a. Should be detailed b. Should be given to others for review and comments c. Sets out the rationale for a research study d. All of the above 70. The Introduction section of the research plan a. Gives an overview of prior relevant studies b. Contains a statement of the purpose of the study c. Concludes with a statement of the research questions and, for quantitative research, it includes the research hypothesis d. All of the above 71. According to your text, which of the following is not a source of research ideas? a. Everyday life b. Practical issues c. Past research d. Theory e. All of the above 72. A review of the literature prior to formulating research questions allows the researcher to do which of the following? a. To become familiar with prior research on the phenomenon of interest 184 b. To identify potential methodological problems in the research area c. To develop a list of pertinent problems relative to the phenomenon of interest d. All of the above 73. If a baseball coach calculates batting averages, what scale would be used? a. Interval scale b. Ratio scale c. Nominal scale d. Ordinal scale 74. The number of police officers and the number of crimes are positively related. This relationship is: a. A causal relationship b. A direct relationship c. A probabilistic causal relation d. A spurious relationship 75. Partial correlation analysis involves: a. Examining the relationship between two or more variables controlling for additional variables statistically b. Including only one group in a correlational analysis c. Matching participants on potential confounding variables d. Limiting the sample to individuals at a constant level of an extraneous variable Fundamentals of Research Methodology 185 76. When research is done to test hypotheses and theories about how and why phenomena operate as they do, then the primary purpose of such research is: a. Descri pti ve b. Predictive c. Expl anatory 77. The variable the researcher matches to eliminate it as an alternative explanation is called Variable. a. Matching b. Independent c. Dependent d. Partial 78. Which of the following is not a longitudinal design? a. Panel b. Cross-sectional c. Trend d. Both a and c are longitudinal designs 79. The positive correlation between teachers’ salaries and the price of liquor is a. Spurious b. Due to a third-variable c. Nonspurious d. Both a and b 186 80. Which of the following is considered a special case of the general linear model? a. A variable b. Partial correlation c. Analysis of covariance d. Both b and c 81. When a researcher starts with the dependent variable and moves backwards, it is called a. Predictive research b. Retrospective research c. Exploratory research d. Descriptive research 82. The method of working multiple hypotheses refers to a technique for identifying rival explanations. a. True b. False 83. GLM refers to which of the following? a. General Logit Model b. General Limited Model c. General Lab Model d. General Linear Model Fundamentals of Research Methodology 187 84. The post hoc fallacy is . a. Maki ng the argument that because A preceded B, A must have caused B b. Maki ng the argument that because A preceded B, A and B must be correlated c. Making the argument that because A preceded B, they cannot be correlated d. None of the above 85. Which one of the following is not a step in non-experimental research? a. Determine research problem and hypotheses b. Analyze data c. Interpret results d. All are steps 86. If a research finding is statistically significant, then a. The observed result is probably not due to chance b. The observed result cannot possibly be due to chance c. The observed result is probably a chance result d. The null hypothesis of “no relationship” is probably true 188 87. Which of the following is/are necessary condition(s) for causation? a. The relationship condition b. The temporal antecedence condition c. The lack of alternative explanation condition d. All of the above 88. Which of the following independent variables cannot be manipulated in a research study? a. Gender b. Ethnicity c. Intelligence and other traits d. None of ht above can be manipulated in a research study 89. Non-experimental research in which the primary independent variable of interest is categorical is sometimes called a. Causal-comparative research b. Correlational research 90. Which approach is the strongest for establishing that a relationship is causal? a. Causal-comparative b. Correlational c. Experimental d. Historical Fundamentals of Research Methodology 189 91. ________ is the most commonly used technique for controlling for extraneous variables in nonexperimental research. a. Matching b. Holding extraneous variables constant c. Statistical control d. Static control 92. It is best to use the method of working multiple hypotheses when a. You are finished with your research b. You are planning your research study c. You are hoping to publish your already obtained research results d. None of the above 93. Matching can be done when your independent variable is categorical or quantitative. a. True b. False 94. If a correlation coefficient is .96, we would probably be able to say that the relationship is a. Weak b. Strong c. Statistically significant d. b is true and c is probably true 190 95. Which of the following symbols represents a population parameter? a. SD b. σ c. r d. 96. If you drew all possible samples from some population, calculated the mean for each of the samples, and constructed a line graph (showing the shape of the distribution) based on all of those means, what would you have? a. A population distribution b. A sample distribution c. A sampling distribution d. A parameter distribution 97. What does it mean when you calculate a 95% confidence interval? a. The process you used will capture the true parameter 95% of the time in the long run b. You can be “95% confident” that your interval will include the population parameter c. You can be “5% confident” that your interval will not include the population parameter d. All of the above statements are true Fundamentals of Research Methodology 191 98. What would happen (other things equal) to a confidence interval if you calculated a 99 percent confidence interval rather than a 95 percent confidence interval? a. It will be narrower b. It will not change c. The sample size will increase d. It will become wider 99. Which of the following statements sounds like a null hypothesis? a. The coin is not fair b. There is a correlation in the population c. There is no difference between male and female incomes in the population d. The defendant is guilty 100. The analysis of variance is a statistical test that is used to compare how many group means? a. Three or more b. Two or more 101. What is the standard deviation of a sampling distribution called? a. Sampling error b. Sample error c. Standard error d. Simple error 192 102. Hypothesis testing and estimation are the two key branches of the field of inferential statistics? a. True b. False 103. A ______ is a subset of a _________. a. Sample, population b. Population, sample c. Statistic, parameter d. Parameter, statistic 104. A _______ is a numerical characteristic of a sample and a ______ is a numerical characteristic of a population. a. Sample, population b. Population, sample c. Statistic, parameter d. Parameter, statistic 105. A sampling distribution might be based on which of the following? a. Sample means b. Sample correlations c. Sample proportions d. All of the above Fundamentals of Research Methodology 193 106. As a general rule, researchers tend to use ____ percent confidence intervals. a. 99% b. 95% c. c. 50% d. none of the above 107. Which of the following is the researcher usually interested in supporting when he or she is engaging in hypothesis testing? a. The alternative hypothesis b. The null hypothesis c. Both the alternative and null hypothesis d. Neither the alternative or null hypothesis 108. When p<.05 is reported in a journal article that you read for an observed relationship, it means that the author has rejected the null hypothesis (assuming that the author is using a significance or alpha level of .05). a. True b. False 109. When p>05 is reported in a journal article that you read for an observed relationship, it means that the author has rejected the null hypothesis (assuming that the author is using a significance or alpha level of .05). a. True b. False 194 110. _________ are the values that mark the boundaries of the confidence interval. a. Confidence intervals b. Confidence limits c. Levels of confidence d. Margin of error 111. _____ results if you fail to reject the null hypothesis when the null hypothesis is actually false. a. Type I error b. Type II error c. Type III error d. Type IV error 112. A good way to get a small standard error is to use a ________. a. Repeated sampling b. Small sample c. Large sample d. Large population 113. Identify which of the following steps would not be included in hypothesis testing. a. State the null and alternative hypotheses b. Set the significance level before the research study c. Eliminate all outliers d. Obtain the probability value using a computer program such as SPSS e. Compare the probability value to the significance level and make the statistical decision Fundamentals of Research Methodology 195 114. A ________ is a range of numbers inferred from the sample that has a certain probability of including the population parameter over the long run. a. Hypothesis b. Lower limit c. Confidence interval d. Probability limit 115. ________ is the standard deviation of a sampling distribution. a. Standard error b. Sample standard deviation c. Replication error d. Meta error 116. An effect size indicator is a statistical measure of the strength of a relationship. a. True b. False 117. Which of the following can be viewed as an effect size indicator? a. r-squared b. r c. Eta-squared d. Omega-squared e. All of the above 196 118. When the researcher rejects a true null hypothesis, a ____ error occurs. a. Type I b. Type A c. Type II d. Type B 119. The use of the laws of probability to make inferences and draw statistical conclusions about populations based on sample data is referred to as ___________. a. Descriptive statistics b. Inferential statistics c. Sample statistics d. Population statistics 120. A statistical test used to compare 2 or more group means is known as _____. a. One-way analysis of variance b. Post hoc test c. t-test for correlation coefficients d. Simple regression 121. A statistical test used to determine whether a correlation coefficient is statistically significant is called the ___________. a. One-way analysis of variance b. t-test for independent samples c. Chi-square test for contingency tables d. t-test for correlation coefficients Fundamentals of Research Methodology 197 122. The cutoff the researcher uses to decide whether to reject the null hypothesis is called the: a. Significance level b. Alpha level c. Probability value d. Both a and b are correct 123. __________ is the failure to reject a false null hypothesis. a. Type I error b. Type II error c. Type A error d. Type B error 124. Which of the following statements is/are true according to the logic of hypothesis testing? a. When the null hypothesis is true, it should be rejected b. When the null hypothesis is true, it should not be rejected c. When the null hypothesis is false, it should be rejected d. When the null hypothesis is false, it should not be rejected e. Both b and c are true 125. What is the key question in the field of statistical estimation? a. Based on my random sample, what is my estimate of the population parameter? b. Based on my random sample, what is my estimate of normal distribution? 198 c. Is the value of my sample statistic unlikely enough for me to reject the null hypothesis? d. There is no key question in statistical estimation 126. Assuming innocence until “proven” guilty, a Type I error occurs when an innocent person is found guilty. a. True b. False 127. This is the difference between a sample statistic and the corresponding population parameter. a. Standard error b. Sampling error c. Difference error d. None of the above 128. The “equals” sign (=) is included in which hypothesis when conducting hypothesis testing? a. Null b. Alternative c. It can appear in both the null and the alternative hypothesis 129. A Type I error is also known as a ______. a. False positive b. False negative c. Double negative d. Positive negative Fundamentals of Research Methodology 199 130. A Type II error is also known as a ______. a. False positive b. False negative c. Double negative d. Positive negative 131. If a finding is statistically significant one must also interpret the data, calculate an effect size indicator, and make an assessment of practical significance. a. True b. False 132. The p-value used in statistical significance testing should be used to assess how strong a relationship is. For example, if relationship A has a p=.04 and relationship B has a p=.03 then you can conclude that relationship B is stronger than relationship A. a. True b. False 200 Multiple choice question answer 1. Mall intercept interviews 2. Wide Area Telecommunications Service 3. Questionnaire 4. Questionnaire design 5. Double barreled question 6. Response rate 7. Funnel technique 8. Both A & B 9. Respondents are willing to co-operate 10. Self-administered questionnaires 11. Arithmetic mean, median, mode 12. All of the above 13. Researcher’s degree of confidence 14. Quasi- experimental design 15. Frequency 16. Sometime documents provide incomplete account to the researcher 17. Moderate 18. Loaded question 19. Judgmental sampling 20. Both A & B 21. Abstraction 22. Variables 23. Mall intercept interviews 24. Funnel technique 25. Field interview 26. Experiment 27. A tentative statement about the relationship 28. All of the above 29. Knowledge accumulates and learns from the work of others 30. All of the above 31. A research proposal is an unorganized and unplanned project 32. Exploratory research 33. Primary data 34. To generate the hypothesis 35. Both A & B Fundamentals of Research Methodology 201 36. Coding 37. Interim analysis 38. Memoing 39. Correlational 40. Factsheets codes 41. Hierarchical category system 42. A priori codes 43. Enumeration 44. Interim analysis 45. Mixed research 46. Qualitative research 47. An attempt to confirm the researcher’s hypotheses 48. A variable 49. Independent variable 50. It rarely is conducted in a controlled setting or environment 51. Experimental Research 52. Manipulation of the independent variable 53. Causal-comparative and correlational research 54. Several variables never change 55. Mixed method research 56. Experimental research 57. Both a and b 58. An extraneous variable 59. Causal-comparative research 60. Annual income 61. Control group 62. Jumping to the conclusion of causality 63. Experimental 64. -1.00 65. Positive 66. All of the above 67. b and c 68. Are often generated as the data are collected, interpreted, and analyzed 69. All of the above 70. All of the above 71. Past research 72. All of the above 73. Ratio scale 74. A spurious relationship 75. Examining the relationship between two or more variables 202 controlling for additional variables statistically 76. Expl anatory 77. Matching 78. Both a and c are longitudinal designs 79. Both a and b 80. Both b and c 81. Retrospective research 82. True 83. Linear Model 84. Maki ng the argument that because A preceded B, A must have caused B 85. All are steps 86. The observed result is probably not due to chance 87. All of the above 88. None of ht above can be manipulated in a research study 89. Causal-comparative research 90. Experimental d. Historical 91. Statistical control 92. You are planning your research study 93. True 94. b is true and c is probably true 95. σ 96. A sampling distribution 97. All of the above statements are true 98. It will become wider 99. There is no difference between male and female incomes in the population 100. Two or more 101. Standard error 102. True 103. Sample, population 104. Statistic, parameter 105. All of the above 106. 95% 107. The alternative hypothesis 108. True 109. False 110. Confidence limits 111. Type II error 112. Large sample 113. Eliminate all outliers Fundamentals of Research Methodology 203 114. Confidence interval 115. Standard error 116. True 117. All of the above 118. Type I 119. Inferential statistics 120. One-way analysis of variance 121. T-test for correlation coefficients 122. Significance level 123. Type II error 124. Both b and c are true 125. Based on my random sample, what is my estimate of the population parameter? 126. True 127. Sampling error 128. Null 129. False positive 130. False negative 131. 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