Bayesian Modeling with R and Stan

Our next Meetup will be downtown at Neumont College. City Creek has free two hour parking or you can take the Trax blue or green line to the Gallivan Plaza or City Center stations.

Recent advances in Markov Chain Monte Carlo (MCMC) simulation have led to the development of a high-level probability modeling language called Stan. In this presentation, Sean Raleigh will give a gentle introduction to Bayesian inference using R and Stan.

Sean Raleigh received his Ph.D. in mathematics from U.C. San Diego, specializing in geometric topology and knot theory. He is a professor of mathematics at Westminster College and currently chairs the data science program. As part of Sean's professional work, he advocates for Bayesian methods in data analysis and co-directs QUARC, the Quantitative Analysis and Research Cooperative.

The meeting will be live streamed on YouTube on the Utah R Users Group channel.