Skip to main content

LAKERS TOGETHER: View the university’s COVID-19 response, including plans for returning to campus for Winter 2021. Also, be sure to complete the online daily self-assessment.

2018-2019 Undergraduate & Graduate Catalog

Search Help

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



If you are in need of assistance please submit any questions or comments.