A review of multiple regression including assumptions, estimation and inference, diagnostics, and modelling with factors. Variable selection techniques including cross-validation. Smoothing techniques, generalized additive models, and the incorporation of random effects and/or serial auto-correlated error structures.

Prerequisite(s): Statistical Sciences 3859A/B.

Extra Information: 3 lecture hours.