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
- Teacher: Mohan Delampady