STAT 544 Bayesian Statistics

This website is designed to host course material for STAT 544 - Bayesian Statistics at Iowa State University.

Textbook

The required textbook for the course is Bayesian Data Analysis (3rd edition).

Some other introductory suggestions are linked below:

• Doing Bayesian Data Analysis
• A First Course in Bayesian Statistical Methods
• Bayesian Computation with R
• The Bayesian Choice
• Bayesian Essentials with R

Software

This course will utilize the statistical software R and the Bayesian software Stan.

Some links to other Bayesian statistical software is provided on the software page.

Relevant course pages

• Applets
• Slides
• Previous midterms
• Report
• Youtube Videos
• Catalog of default priors

Course Description

Specification of probability models; subjective, conjugate, and noninformative prior distributions; hierarchical models; analytical and computational techniques for obtaining posterior distributions; model checking, model selection, diagnostics; comparison of Bayesian and traditional methods.

Course Objectives

Students passing this course will be able to

• Explain the basics of a Bayesian analysis including prior, likelihood, and posterior.
• Derive a conjugate Bayesian analysis with Jeffreys prior.
• Implement a computational Bayesian analysis using JAGS or Stan.

Prerequisite

The prerequisite for the course is previous or concurrent enrollement in STAT 543 or equivalent, e.g. Econ 672.

Q&A

Please use the Canvas discussion forum.

Reading schedule

See slides page.

Faculty Senate Recommendations

This course abides by the Center for Excellence in Learning and Teaching recommended syllabi statements.