LP-AE - MA2266LESSON PLAN LP Rev. No: 00 Sub Code & Name: MA 2266 STATISTICS AND NUMERICAL METHODS Unit: III Branch: AE&ME Date: 4.12.2009 Semester : IV Page 1 of 6 DOC/LP/01/28.02.02 Unit syllabus: SOLUTION OF EQUATIONS AND EIGENVALUE PROBLEMS Newton-Raphson method- Gauss Elimination method – Pivoting - Gauss-Jordan methods – Iterative methods of Gauss-Jacobi and Gauss-Seidel - Matrix Inversion by Gauss-Jordan method Eigenvalues of a matrix by Power method . Objective: To find numerical solutions to system of linear equations and transcendental equations. Session No 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Topics to be covered Teaching Method Time Ref Newton-Raphson method 50m 2,5,6 BB Newton-Raphson method 50m 2,5,6 BB Gauss Elimination method 50m 2,5,6 BB Gauss Elimination method 50m 2,5,6 BB Gauss-Jordan method 50m 2,5,6 BB Gauss- Jacobi method 50m 2,5,6 BB Gauss- Jacobi method 50m 2,5,6 BB Gauss-Seidel method 50m 2,5,6 BB Gauss-Seidel method 50m 2,5,6 BB Matrix Inversion by Gauss-Jordan method 50m 2,5,6 BB Eigenvalues of a matrix by Power method 50m 2,5,6 BB Tutorial 50m 2,5,6 BB 1 5. 17.5. 23. 16. Objective: To acquire the knowledge of finding numerical values of differentiations and integrations. Problems 50m 2.5. 50m 2.02 LP-AE .6 BB Newton’s divided difference formula for unequal intervals.MA2266 LESSON PLAN LP Rev. 15. 18. 20.6 BB Double integration by Trapezoidal method.6 BB Lagrange’s interpolation formula for unequal intervals. Session No 13. 22. NUMERICAL DIFFERENTIATION AND NUMERICAL INTEGRATION Lagrange’s and Newton’s divided difference interpolation –Newton’s forward and backward difference interpolation .5.DOC/LP/01/28.02. Numerical differentiation and Integration.6 BB 50m 2. No: 00 Sub Code & Name: MA 2266 STATISTICS AND NUMERICAL METHODS Unit: IV Branch: AE&ME Date: 4. Topics to be covered Teaching Method Time Ref Introduction: Interpolation.5.6 BB Simpson’s 1/3 rule and problems 50m 2.6 BB 50m 2. 50m 2.6 BB 2 .5.6 BB 50m 2.5. 14.12.Approximation of derivatives using interpolation polynomials . 19. 21.5. 50m 2.5.Numerical integration using Trapezoidal and Simpson’s 1/3 rules.5.6 BB Problems in Numerical Differentiation (Newton forward formula) Problems in Numerical Differentiation (Newton backward formula) Problems in Numerical Differentiation (Newton forward formula) Problems in Numerical Differentiation (Newton divided difference formula) CAT – I 75m Numerical Integration by Trapezoidal rule and problems 50m 2.2009 Semester : IV Page 2 of 6 Unit syllabus: INTERPOLATION.6 BB 50m 2. 5.6 BB CAT – II 75m Milne’s predictor-corrector methods for solving first order equations Milne’s predictor-corrector methods for solving first order equations 3 .2009 Semester : IV Page 3 of 6 Unit syllabus: NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS Taylor’s series method . Objective: To know how to solve the ODE numerically.02. 35.5.Milne’s predictor-corrector methods for solving first order equations . 32. Session No 25.5.Fourth order Runge-Kutta method for solving first and second order equations . Simpson’s Problems 50m 2.02 LP-AE .6 BB Modified Euler’s method 50m 2.Euler’s method .6 BB Finite difference methods for solving second order equation 50m 2.6 BB Euler’s method 50m 2.6 BB Fourth order Runge-Kutta method for solving first order equations Fourth order Runge-Kutta method for solving second order equations 50m 2.12.24.6 BB 50m 2.6 BB DOC/LP/01/28.5. 29. Double integration by method.5.5.6 BB Finite difference methods for solving second order equation. 27. 34.5. 26. 33.5.6 BB 50m 2. Topics to be covered Teaching Method Time Ref Taylor’s series method 50m 2. 30. 31.MA2266 LESSON PLAN LP Rev. No: 00 Sub Code & Name: MA 2266 STATISTICS AND NUMERICAL METHODS Unit: V Branch: AE&ME Date: 4. 28. 36.5.5.Modified Euler’s method . 50m 2.Finite difference methods for solving second order equation.5.6 BB Taylor’s series method 50m 2.5.6 BB 50m 2.6 BB Tutorial 50m 2. 4 BB Testing of Hypothesis for variance 50m 1. 39.3.4 BB Testing of Hypothesis for population mean and sample mean 50m 1. Teaching Method Topics to be covered Time Ref Introduction Sampling. Proportion.3.4 BB Student –t-test(two sample means) 50m 1.4 BB Testing of Hypothesis for variance 50m 1. No: 00 Sub Code & Name: MA 2266 STATISTICS AND Unit: I NUMERICAL METHODS Date: 4. 44.4 BB Chi-square test(goodness of fit) 50m 1.4 BB F-test between variances 50m 1.3.2009 Branch: AE&ME Page 4 of 6 Semester : IV Unit syllabus: TESTING OF HYPOTHESIS Sampling distributions . 47. Testing of Hypothesis 20m 30m 1. 38.12. 41.3.4 BB Tutorial 50m 1. 40.3. Session No 37.4 BB Testing of Hypothesis for two sample means 50m 1.MA2266 LESSON PLAN LP Rev.3. 46. 43.3.4 BB Chi-square test(independence of attributes) 20m 30m 1. Objective: To know about large and small sample test.4 BB Testing of Hypothesis for proportions 50m 1.3.3.3. 42.02. 48.DOC/LP/01/28.4 BB Student –t-test(population mean and sample mean) 50m 1.3.3.02 LP-AE.4 BB 4 .Tests for single mean. Difference of means (large and small samples) – Tests for single variance and equality of variances – chi-square test for goodness of fit – Independence of attributes. 45. 3.02.12.3.4 BB 22 -factorial design.2 2 -factorial design.3.4 BB ANOVA One way classification 50m 1. 57.3. 50m 1. Objective: To know about design of experiments.4 BB Latin square design 50m 1.4 BB CAT – III 75m 5 .2009 Branch: AE&ME Page Semester : IV 5 of 6 Unit syllabus: DESIGN OF EXPERIMENTS Completely randomized design – Randomized block design – Latin square design . 50.02 LESSON PLAN LP-AE LP Rev. 56. Topics to be covered Teaching Method Time Ref Introduction to the design of experiments 50m 1. Session No 49.4 BB ANOVA Two way classification 50m 1.4 BB Randomized block design 50m 1.3. 51.4 BB Latin square design 50m 1.MA2266 NUMERICAL METHODS Date: 4.3.4 BB Tutorial 50m 1. 53.3. 60. 59.3.3.4 BB Randomized block design 50m 1. 58.4 BB Completely randomized design 50m 1.4 BB Completely randomized design 50m 1. 54.3. No: 00 Sub Code & Name: MA 2266 STATISTICS AND Unit: II .3.DOC/LP/01/28. 52. 55. “Probability and Statistics for Engineers and Scientists”. Myers. 6 th Edition. 5 th Edition. R.. Johnson and C. P. 2.H. Myers. References: 3. Tata McGraw Hill edition. “Applied Numerical Analysis”.MA2266 LESSON PLAN LP Rev. “Schaum’s Outlines Probability and Statistics”. 5. and Wheatley. Spiegel.12. Pearson Education. C and Canale. “ Numerical methods in Engineering and Science”.A.B.A.02 LP. 2006. New Delhi. 2004. and K Ye. New Delhi. 8th edition. C. 7th edition.. Srinivasan.J.AE . R.02. 4. 2007. Pearson Education Asia. R. Khanna Publishers.E. Prepared by Approved by M RADHAKRISHNAN Dr R MUTHUCUMARASWAMY Senior Lecturer Professor & Head Department of Applied Mathematics Signature Name Designation 6 . No: 00 Sub Code & Name: MA 2266 STATISTICS AND NUMERICAL METHODS Branch: AE&ME Date: 4. Chapra. 2004. Gupta.S.L. 2007 (For units 3. Tata McGraw-Hill. B. Pearson Education. S. “Numerical Methods for Engineers”. New Delhi. M. Schiller and R. J. O. Asia. 4 and 5). Grewal. Gerald.R. S. and Grewal.2009 Page Semester : IV 6 of 6 Course Delivery Plan: Week 1 I II 3 4 I II I II I II 5 6 7 8 9 10 11 12 13 14 15 I II I II I II I II I II I II I II I II I II I II I II CAT-III CAT-II CAT-I Units 2 TEXT BOOKS 1.DOC/LP/01/28. 6th Edition. F. “Miller and Freund’s Probability and Statistics for Engineers”. 2007. P.S. Asia . R. Walpole. 6.