MATH 4345 Bayesian Statistics

This three-hour course covers the theory and basic applications of Bayesian inference. The course covers
topics such as prior and posterior distributions, model checking, and the use of software algorithms to
simulate and perform inference on Markov chains for a specified model. Data analysis and simulation will
be performed using software packages such as R and MatLab.

Prerequisite

MATH 3333