Department of MathematicscoretheorySem 3
MULTIVARIATE ANALYSIS
MAT 3131
Syllabus
- 01Multivariate distributions: multivariate normal distribution and its properties, distributions of linear and quadratic forms, tests for partial and multiple correlation coefficients and regression coefficients and their associated confidence regions. Data analytic illustrations
- 02Wishart distribution (definition, properties), construction of tests, union-intersection and likelihood ratio principles, inference on mean vector, Hotelling's T2
- 03MANOVA- Inference on covariance matrices
- 04Classification methods: Discriminant analysis, principal component analysis and factor analysis, Canonical Correlation analysis, Correspondence Analysis, Multidimensional Scaling, Cluster analysis
- 05Nonparametric and robust methods of multivariate analysis
- 06Graphical representation of multivariate data
References
- T. W. Anderson (2009), An Introduction to Multivariate Statistical Analysis. (third edition). John Wiley & sons.
- Richard Arnold Johnson and Dean W. Wichern (2007) Applied Multivariate Statistical Analysis, Prentice Hall.
- Alvin C. Rencher, William F. Christensen (2012), “Methods of Multivariate Analysis” John Wiely.
- Rao, C. R. (2002). Linear Statistical Inference and its Applications. (second edition) (Wiley Series in Probability and Statistics)
- Mathematical Statistics, Basic Ideas and Selected Topics, Volumes I-II Package By Peter J. Bickel, Kjell A. Doksum (2015). (CRC Press) (second edition)
- C. Casella and R. L. Berger: Statistical Inference, 2nd Edition (2007) Cengage Learning.
Credits Structure
3Lecture
0Tutorial
0Practical
3Total