This course aims to provide students with a solid background in applications of Bayesian methods as well as regression and time series analysis at an advanced graduate level. The course covers the Bayesian methods for inference as well as basic techniques of both the linear model, generalized linear model, non-linear models, as well as various time series methods. Emphasis is placed on appropriate model selection, usage of statistical software, and interpretation of results. categorical data techniques, and bayesian methods for inference

Prerequisite: (STAT4230 or STAT4250 or STAT 5100) or approval from program director.