June 10-12 Short Courses

Introduction to Bayesian Analysis

Dr. Steve Culpepper

Course Description

This short course introduces the concepts and methodology of Bayesian statistics. Topics include Bayes’ rule, likelihood functions, prior and posterior distributions, Bayesian point estimates and intervals, Bayesian hypothesis testing, and prior specification. Additional topics include Bayesian regression, model selection, prediction, diagnostics, Bayes factors, and exploratory factor analysis. We also review practical implementations of Markov chain Monte Carlo and hierarchical models using R and JAGS and discuss conceptual differences between the Bayesian and frequentist paradigms.

Event Information

June 10-12, 2024

Mon/Tue: 8:30 a.m. – 5:00 p.m. EDT
Wed: 8:30 a.m. – 12:00 p.m. EDT

Wayne State University
Mike Ilitch School of Business

Meet the Instructor

Steven Andrew Culpepper is a Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign. His research focuses on understanding complex data patterns, especially in areas like educational testing and psychological assessment. He earned his BS in Economics from Bowling Green State University in 2001 and completed his PhD in Educational Psychology at the University of Minnesota in 2006. Culpepper’s expertise lies in multivariate categorical data, latent class models, longitudinal latent structure models, and large-scale testing and assessment.

Video Introduction