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/STAT 370 - Probability or STAT 290 - Statistics).
Credit(s): 3
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