STAT 8310 - Bayesian Data Analysis

3 Credit Hours
Prerequisites: Math 4752/MATH 6752 (Mathematical Statistics II) or equivalent, and R programming.
Description
This course will cover the topics in the theory and practice of Bayesian statistical inference, ranging from a review of fundamentals to questions of current research interest. Motivation for the Bayesian approach. Bayesian computation, Monte Carlo methods, asymptotics. Model checking and comparison. A selection of examples and issues in modeling and data analysis. Discussion of advantages and difficulties of the Bayesian approach. This course will be computationally intensive through analysis of data sets using the R statistical computing language.