This unit starts with the classical normal linear regression model. The family of generalized linear models is then introduced and maximum likelihood estimators are derived. Models for counted responses, binary responses, continuous non-normal responses and categorical responses; and models for correlated responses, both normal and non-normal, and generalized additive models, are studied. All models and methods are illustrated using data sets from disciplines such as biology, actuarial studies and medicine. SAS software is used. -- Course Website
Instructor: Associate Professor Gillian Heller
Prerequisites: Admission to MAppStat or PGDipAppStat or PGCertAppStat
