STAT 6574 - Introduction to Bayesian Statistics

This is an introductory-level class in Bayesian methods. Students will become comfortable with the language and meaning of a Bayesian approach to inference. The class will be applied in nature (not mathematical) and will use R (so it won't be a programming class). Students will be introduced to the three basics steps related to Bayesian statistical inference: (a) learning and estimating parameter(s) that seek to explain some phenomenon, (b) creating models based on estimation of parameter(s), and (c) comparing models for effective model selection. These steps will be applied in various “typical” problem types and students will learn the effective application using R.