Course Description
Focus is on the generalized linear model (GLM) for cases when variables have specific non-normal conditional distributions, with emphasis on common data analytic challenges that arise in real world settings. Topics include nonlinear relationships, nominal and ordinal outcomes, discrepant data, and bootstrapping methods. Course materials are grounded in applied examples from the social and health sciences.
