Syllabus: Multivariate normal distribution, Transformations
and quadratic forms; Review of matrix algebra involving projection
matrices and matrix decompositions; Linear
models; Regression and Analysis of variance;
General linear model, Matrix formulation, Estimation in linear model,
Gauss-Markov theorem, Estimation of error variance, Testing in the
linear model, Regression, Partial and multiple correlations, Analysis of
variance,
Multiple
comparisons; Stepwise regression, Regression diagnostics.
Reference Texts:
1. Sanford Weisberg: Applied Linear Regression
2. C R Rao: Linear Statistical Inference and Its Applications
3. George A F Seber and Alan J Lee: Linear Regression Analysis
https://www.isibang.ac.in/~adean/infsys/database/Bmath/S3.html
- Teacher: Mohan Delampady