Table of contents1. Executive summary……………………………………………………………………………… ……………. 2. Key performance indicators/Variables……………………………………………………………….. Age of properties against time …………………………………………………………………………… Distance frequency distribution for properties being sold…………………………………. Type of properties sold…………………………………………………………………………………… …. Performance of each sales agent……………………………………………………………………….. Customer Satisfaction………………………………………………………………………… N ……………… - Graphical a analysis…………………………………………………………………………… m …………….. e - Hypothesis : testing…………………………………………………………………………… S …………… h 3. Recommendations and a Conclusion……………………………………………………………………… i r a R a h Executive Summary 1 | Page .. 6 3.Hypothesis testing……………………………………………….. 5 - Graphical analysis………………………………………………… 5 .Shaira Rahman (z5059151) Table of contents 1. Key performance indicators/variables……………………………………… 1 Age of property and time…………………………………………………………… 2 Distance for properties being sold and time………………………………. Executive summary…………………………………………………………………. Recommendations and conclusion……………………………………………… 7 1. 4 Performance of each sales agent………………………………………………… 4 Customer satisfaction…………………………………………………………………. 2 Type of properties sold………………………………………………………………. 1 2. 0 Age This histogram in this figure displays the age frequencies of the properties sold by BreezyRealty. BreezyRealty wanted to determine continual running of business and likelihood of receiving “word-to-mouth” referrals and the expectancy of at least 80% of customers presented in the data to be satisfied or very satisfied with this agency. a real estate agency company based at the eastern suburbs. Also.0 293. as shown in the summary statistics table on the side.0 3. the performance of 4 sales agents were compared against one another. The finding made suggest that the properties ages around 12 years and the closer proximity to the beach had the most likelihood of being sold.Shaira Rahman (z5059151) This report has been prepared by Crunch-It Consultants on behalf of BreezyRealty.0 13. Other variables such as time taken to sell properties were tested against their ages and proximities from the beach.0 3. The different types of properties were also displayed in a pie chart. It provides analysis of 6 variables of customer/agent data from a sample of 293 customers who chose to sell their properties with BreezyRealty real estate. the unimodal frequency distribution shows that most of the properties sold are around 12 years with a total frequency of 127 properties sold out of the total 293 sold.1 10. Key Performance Indicators/Variables Age of properties sold and time Figure 1 age Frequency Distribution: Age of Properties Sold 150 100 Frequency Frequency 50 0 3 6 9 12 15 Mean Median Mode SD Range Minimum Maximum Count 8. In addition.0 9. Figure 2 2 | Page .6 9. the distribution does not appear to be symmetrical and does not have any outliers. out of which agent 2 was perceived as the underperforming employee. Specifically. 2. It is skewed to the left meaning that the mean is less than the median. Also. 0 3990.0 3990.38 R² = 0.0 293.0 . A gap in this scatter plot indicates that there are no properties sold that are aged between 4 to 8 years. figure 5 displays ages of properties and time having a correlation coefficient of 0.0 2527.Shaira Rahman (z5059151) Age vs Time Taken to Sell Property 140 120 100 80 Time (days) 60 Linear () 40 f(x) = 0.0805.0 19995. Distance for properties being sold and time Figure 3 distanc e Mean Median Mode SD Range Minimum Maximum Count 3 | Page 2687. the more likely they are at being sold.37x + 29.7 19934. There is a trend which displays that the older the houses are. There is also a trend line and regression presented in the legend of the graph.0 61.01 20 0 2 4 6 8 10 12 14 Age (years) This scatter plot illustrates the relationship between ages of properties against the time it takes to sell properties depending on how old they are. Additionally. There is also a gap in the data suggesting the properties further than 12000 metres away from the beach are not included in the selling range and the distance of 20000 metres appears to be an outlier.95 R² = 0 0 0 10000 20000 30000 Distance (m) This scatter plot demonstrates the relationship between distances of properties from the beach and the time it takes to sell properties depending on their proximities. there is also an outlier presented in this plot where the properties that are further away from the beach are less likely at being 4 | Page . The modal class in this histogram is 2000 metres from the beach meaning that the closer the houses are from the beach. There is a trend which outlines that the closer the properties are to the beach. the more likely they are at being sold.Shaira Rahman (z5059151) Distance from the beach for the properties being sold 140 120 100 80 60 Frequency 40 20 0 Frequency Distance (m) This histogram portrays the frequency of distance from the beach for the properties sold with BreezyRealty. Conversely. the more likely they are at being sold. Figure 4 Distance from Beach vs Time Taken to Sell Property 140 120 100 80 Time (days) Linear . The distribution of the histogram is positively skewed meaning the mean is greater than the median.Time 60 40 20 f(x) = 0x + 31. Figure 5 Correlation Coefficients for Age vs Distance vs Time Distance (m) Distance (m) Time Age 1 0. Also. Houses are the least common type of property sold in the eastern suburbs. it is evident that the most common type of property being sold are town houses.0805 1 Type of properties sold Figure 6 Type of property sold 1=unit 11% 28% 2=town house 3= house 61% From the findings presented by this pie chart. Figure 5 indicates that distance and time has a 0. accounting for 11% of customers from the data.Shaira Rahman (z5059151) sold.0389 correlation coefficient.0071 Time Age 1 0. accounting for 61% of the customers from the data. Performance of each sales agent Figure 7 5 | Page .0389 0. In turn it outlines their overall performance. it can be said that agent 2 has sold 63 properties. Also. the new total for customer satisfaction is 280. Customer 6 | Page . agent 4 has been shown to have sold the highest amount of properties (80). the least amount relative to his/her peers out the sample of 293 customers’ data. From the data above.Shaira Rahman (z5059151) Individual relative performance of BreezyRealty sales agents 90 80 70 60 Number of properties sold 50 frequency 40 30 20 10 0 Sales Agents This column graph expresses the number of properties sold by each individual agent. Customer satisfaction - Graphical analysis Figure 8 Percentage of customer satisfaction 18%3%17% 1= very dissatisfied 2= dissatisfied 3= satisfied 4= very satisfied 63% This pie chart displayed above was used to test the satisfaction variable which contains categorical and ordinal data ranging from 1= very dissatisfied to 4=very satisfied and there is an additional category ‘9=no response’ which was discarded from summary statistics because it provided no statistical value. By rejecting the no responses in these statistics. 29 is greater than -1.05 = .8 z= √ 0.645 Therefore. The sample proportion was calculated as: ṗ= x n ṗ= 226 280 ṗ= 0.807 Standardised test statistic: z= √ ṗ−p p (1− p) n 0. The central limit theorem is also being applied in this sample proportion hypothesis testing This was tested using a one tail hypothesis.645.5 (the significance level). a null hypothesis that exactly 80% of the customers were satisfied and an alternative hypothesis that less than 80% of the customers were satisfied.2) 280 z= 0.8 (null hypothesis) H1: P< 0. and therefore does not fall within the rejection region meaning the null hypothesis be failed to be rejected.6141 which is greater than 0.8 (Alternative hypothesis) Taking α= 0. Also.05 (significance level) Z0. H0: P= 0.1. the rejection region is z < . the p value is 0.8(0. - Hypothesis testing This hypothesis has been formulated to test whether there is at least 80% customer satisfaction by BreezyRealty so that they able to repeat business and receive future referrals.Shaira Rahman (z5059151) satisfaction fulfilled the criteria of at least 80% satisfied and this was deduced by a combination of the ‘3 = satisfied’ and ‘4 = very satisfied’ categories with a total of 226 out of 280.29 0.807−0. hence 7 | Page .1.645 There were 280 customers (no responses were excluded) presented from the data provided out of which 226 were customers who were satisfied with the experience they got in selling their properties with BreezyRealty. There is a 95% confidence interval and the data evidently indicates that the null hypothesis will be failed to be rejected. Recommendations and conclusion Through extensive analysis of the data presented by BreezyRealty. 3. more than 80% of the customers out of the sample were either satisfied or very satisfied by selling their properties with BreezyRealty. Crunch-IT recommends BreezyRealty to take the incentive to continue business with the hope of receiving further referral by future customers. Crunch-IT consultants were able to deduce that based on the customer satisfaction levels that were analysed. All the other variables presented in this report will also be taken into consideration to determine what actions to implement.Shaira Rahman (z5059151) the null hypothesis and also the alternative hypothesis that less than 80% of customers are satisfied with BreezyRealty is also considered to be false. 8 | Page .