Bayesian Data Analysis

Many fields of science are transitioning from null hypothesis significance testing (NHST) to Bayesian data analysis. Bayesian analysis provides rich information about the relative credibilities of all candidate parameter values for any descriptive model of the data, without reference to p values. Bayesian analysis applies flexibly and seamlessly to complex hierarchical models and realistic data structures, including small samples, large samples, unbalanced designs, missing data, censored data, outliers, etc. Bayesian analysis software is flexible and can be used for a wide variety of data-analytic models. This course shows you how to do Bayesian data analysis, hands on, with free software called R and JAGS.

This course closely follows the Bayesian estimation framework popularized by Prof. John Kruschke.  We will be using his software, and I strongly recommend both his book (see below) and his blog,

Course Objectives: You will learn

Course Audience: The intended audience is advanced students, faculty, and other researchers, from all disciplines, who want a ground-floor introduction to doing Bayesian data analysis.

Course Prerequisites: No specific mathematical expertise is presumed. In particular, no matrix algebra is used in the course. Some previous familiarity with statistical methods such as a t-test or linear regression can be helpful, as is some previous experience with programming in any computer language, but these are not critical.

Course Topics: (Exact content, ordering, and durations may change due to student interests)

Day 1:

Day 2:

Day 3:

Day 4:

Day 5:

Highly recommended textbook:

Doing Bayesian Data Analysis, 2nd Edition: A Tutorial with R, JAGS, and Stan. The book is a genuinely accessible, tutorial introduction to doing Bayesian data analysis. The software used in the course accompanies the book, and many topics in the course are based on the book. (The course uses the 2nd edition, not the 1st edition.) Further information about the book can be found at

Install software before arriving.

It is important to bring a notebook computer to the course, so you can run the programs and see how their output corresponds with the presentation material.  Please install the software before arriving at the course. The software and programs are occasionally updated, so please check here a week before the course to be sure you have the most recent versions.

For complete installation instructions, please go to