Presenter: Dr. Shirin Golchi, Assistant Professor, McGill University, Canada

This webinar will provide an introduction to basic concepts in Bayesian inference. Topics that will be covered include essential components of Bayesian statistics, estimation and uncertainty quantification in single and multi- parameter linear and generalized linear models, as well as a brief introduction to Bayesian hierarchical modeling and Bayesian computation. The workshop will include examples of parametric inference in R using R-packages that rely on Stan (rstanarm and brms). At the end of this workshops participants will be able to: 1) Specify simple Bayesian models, 2) Make Bayesian inference in single parameter models, and 3) Fit linear and generalized linear models using rstanarm or brms.