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2020-2021 Undergraduate & Graduate Catalog

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STA 421 - Bayesian Data Analysis

An introduction to Bayesian data analysis utilizing the Gibbs Sampler and Metropolis-Hastings algorithm (Markov Chain Monte Carlo method). Estimating posterior distribution parameters, evaluating model effectiveness, hypothesis testing, and bivariate regression modeling. Appropriate computer programs will be used for analysis of real data sets. Offered winter semester on sufficient demand. Prerequisites: STA 312 and MTH 202.

Credits: 3

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