CS 685 - Bayesian Data Analysis

Prerequisite, MATH 361, or equivalent. The main concepts covered in this class include the following: Bayes’ theorem and the Bayesian inferential framework (model specification, model fitting, and model checking), computational methods for posterior simulation integration, regression models, hierarchical models, ANOVA, the Gibbs sampler, Markov chain simulations, and other numerical methods. Letter grade. (Offered as needed.) 3 credits