Estimation and hypothesis testing, and analysis of variance in balanced designs. An introduction to statistical modeling of a univariate response conditional on a set of explanatory variables. Classical formulation of multiple linear regression and analysis of variance. Some discussion of experimental design from power considerations. Selected topics from generalized linear models, nonparametric regression, and quasi-likelihood estimation.
Emphasis is on model building, fitting, validation and subsequent inferences.
Analysis of real data using major statistical software packages. Random walks, discrete time Markov chains, Poisson Process. Further topics such as continuous time Markov chains, branching proceses, renewal theory and estimation in branching processes. Statistical analysis of a multivariate response. Multivariate multiple linear regression, principal components, factor analysis, canonical correlation, discriminant analysis.