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, SAS, Minitab, or MatLab.

Prerequisite

MATH 3332