STAT 430 - Bayesian Analysis

The course covers the fundamental concepts of Bayesian methods including Bayes rule, probability models and prior distributions, and computational and simulation-based methods for deriving posterior distributions and estimating parameters.

Prerequisites: STAT 220 - Fundamentals of Data Science or STAT 250 - Statistical Computing AND STAT 270 - Probability or STAT 290 - Statistics.
Credits: 3
NOTE:
*This course counts toward the 63-hour Liberal Arts and Sciences (LAS) graduation requirement.