Details of MA5108 (Autumn 2022)
Level: 5 | Type: Theory | Credits: 4.0 |
Course Code | Course Name | Instructor(s) |
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MA5108 | Multivariate Analysis | Satyaki Mazumder |
Syllabus |
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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 |
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Statistical Inference (MA4107) |
References |
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Suggested Texts:
1. Anderson, T.W., An Introduction to Multivariate Statistical Analysis, Wiley. 2. Giri, N.C., Multivariate Statistical Analysis, Academic Press. 3. Johnson, R.A. and Wichern, D.W., Applied Multivariate Statistical Analysis, Prentice-Hall of India. 4. Jolliffe, I.T., Principal Component Analysis, Springer. 5. Kshirsagar, A.M., Multivariate Analysis, Marcel Dekker. 6. Rao, C.R., Linear Statistical Inference and Its Applications, Wiley. 7. 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 | MR | 1 | Elective |
5 | MR | 3 | Not Allowed |
6 | MS | 3 | Not Allowed |
7 | MS | 5 | Not Allowed |
8 | MS | 7 | Not Allowed |
9 | MS | 9 | Elective |
10 | RS | 1 | Elective |
11 | RS | 2 | Elective |