Bayesian analysis has become a popular tool for many statistical applications. Yet many data analysts have little training in the theory of Bayesian analysis and software used to fit Bayesian models.
Chuck Huber, Vice President, Stata Corporation will provide an intuitive introduction to the concepts of Bayesian analysis and demonstrate how to fit Bayesian models using Stata. No prior knowledge of Bayesian analysis is necessary and specific topics will include the relationship between likelihood functions, prior, and posterior distributions, Markov Chain Monte Carlo (MCMC) using the Metropolis-Hastings algorithm, and how to use Stata's Bayes prefix to fit Bayesian models. Faculty will learn how Stata statistical software can be used for conducting Bayesian data analysis across a variety of scholarly disciplines.
Chuck Huber, Director of Statistical Outreach at StataCorp and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health
Dr. Larry Price, Director of the Methodology, Measurement and Statistical Analysis (MMSA) at Texas State University and Professor of Psychometrics & Statistics with faculty appointments in the College of Education and Department of Mathematics
This presentation is co-sponsored by the Office of Research and Sponsored Programs and Faculty Development and addresses the university's goal to achieve significant progress in research and creative activity as measured by national standards.
Special Note: The location of this Faculty Focus presentation has been updated. This presentation will be held both in person in Encino Hall 233 and online via Zoom. Participants should only register for the session type they will be attending (in-person or online), not both.