Details of MA5108 (Autumn 2023)
| Level: 5 | Type: Theory | Credits: 4.0 |
| Course Code | Course Name | Instructor(s) |
|---|---|---|
| MA5108 | Multivariate Statistics | Asok Kumar Nanda |
| Syllabus |
|---|
| Distance between two random vectors, multivariate distribution function, generalized variance, properties of multivariate normal distribution and estimation of its parameters, distribution of quadratic forms, spherical and elliptical distributions, Wishart and Hotelling's $T^2$ distributions along with their properties, classification and discriminant analysis, multiple and partial correlation coefficients, principal component analysis, canonical correlations and canonical variables, clustering and factor analysis. |
| Prerequisite |
|---|
| Statistical Inference (MA4107) |
| References |
|---|
| Text Books
Johnson, R.A. and Wichern, D.W. Applied Multivariate Statistical Analysis, PHI Muirhead, R.J. Aspects of Multivariate Statistical Theory, Wiley Reference Books Anderson, T.W. An Introduction to Multivariate Statistical Analysis, Wiley Dyran, B.S. and Odell, P.L. Cluster Analysis, Springer-Verlag Feller, W. An Introduction to Probability Theory, Vol-II, Wiley Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. Multivariate Data Analysis, Cengage. Harville, D.A. Matrix Algebra from A Statistician's Perspective, Springer. Kollo, T. and von Rosen, D. Advanced Multivariate Statistics with Matrices, Springer. Rao, C.R. Linear Statistical Inference and its Applications, Wiley Rencher, L.C. Methods of Multivariate Analysis, Wiley |
Course Credit Options
| Sl. No. | Programme | Semester No | Course Choice |
|---|---|---|---|
| 1 | IP | 1 | Not Allowed |
| 2 | IP | 3 | Not Allowed |
| 3 | IP | 5 | Not Allowed |
| 4 | MP | 1 | Not Allowed |
| 5 | MP | 3 | Not Allowed |
| 6 | MR | 1 | Not Allowed |
| 7 | MR | 3 | Not Allowed |
| 8 | MS | 3 | Not Allowed |
| 9 | MS | 5 | Not Allowed |
| 10 | MS | 7 | Not Allowed |
| 11 | MS | 9 | Elective |
| 12 | RS | 1 | Elective |
| 13 | RS | 2 | Elective |