Course Archives Theoretical Statistics and Mathematics Unit

Course: Introduction to Linear Models and Regression Level: Undergraduate Time: Currently not offered

Syllabus Past Exams Syllabus: i) Multivariate distributions and properties; Multivariate densities; Independence, marginal and conditional distributions; Distributions of functions of continuous random vectors; Examples of multivariate densities: Dirichlet and multivariate normal distributions; Transformations and quadratic forms. ii) Review of matrix algebra involving projection matrices and matrix decompositions; Fisher-Cochran Theorem. iii) Simple linear regression and Analysis of variance. iv) General linear model, Matrix formulation, Estimation in linear model, Gauss- Markov theorem, Estimation of error variance. v) Testing in the linear model, Analysis of variance. vi) Partial and multiple correlations, Multiple comparisons. vii) Stepwise regression, Regression diagnostics. viii) Odds ratios, Logit model. ix) Splines and Lasso. Reference Texts: (a) Sanford Weisberg: Applied Linear Regression. (b) C R Rao: Linear Statistical Inference and Its Applications. (c) George A F Seber and Alan J Lee: Linear Regression Analysis. Top of the page Past Exams

Midterm 23.pdf 24.pdf Semestral 23.pdf 24.pdf Supplementary and Back Paper 23.pdf 24.pdf Top of the page

[ Semester Schedule ][ Statmath Unit ] [Indian Statistical Institute]