Introduction to Bayesian Statistics
** available as of 06/15/2026
** available as of 06/15/2026
Prerequisites: STAT 308.
An introduction to Bayesian data analysis and statistical inference. Topics include single and multiple Bayesian models, hierarchical models, Bayesian linear regression models. The course will also consider computational methods related to Bayesian inference such as Markov Chain Monte Carlo methods. Emphasis is placed on both theoretical understanding and practical implementation using statistical software.
Outcomes: Students will understand the principles of Bayesian inference; implement and evaluate Bayesian models using computational tools; and effectively communicate Bayesian results in applied contexts.
An introduction to Bayesian data analysis and statistical inference. Topics include single and multiple Bayesian models, hierarchical models, Bayesian linear regression models. The course will also consider computational methods related to Bayesian inference such as Markov Chain Monte Carlo methods. Emphasis is placed on both theoretical understanding and practical implementation using statistical software.
Outcomes: Students will understand the principles of Bayesian inference; implement and evaluate Bayesian models using computational tools; and effectively communicate Bayesian results in applied contexts.