Bayesian statistical methods are becoming increasingly popular in a wide variety of modern applications. This workshop provides resources and support for statistics educators to incorporate aspects of Bayesian statistics in their teaching. Through a series of detailed classroom-ready examples and hands-on activities, including exercises in R, participants will learn how to introduce Bayesian ideas into existing statistics courses at each of the introductory, intermediate, and advanced undergraduate levels. Participants will get hands-on experience with conducting Bayesian statistical analysis in R, including regression and hierarchical models. No previous experience with Bayesian statistics is necessary. Although the instructors will share their experiences of incorporating Bayesian ideas in their teaching and provide some suggestions for best practices, this workshop will also be relevant to those interested in a (very) short course in Bayesian statistics.
Presenters: Dr. Jingchen (Monika) Hu, an Associate Professor of Statistics at Vassar College, and Dr. Kevin Ross, a Professor of Statistics at Cal Poly.
Please register here: Introducing Bayesian Statistical Analysis into Your Teaching
Morning session (9am-12noon) will focus on incorporating Bayesian elements in introductory statistics courses
- Module 1: Introduction to Bayesian reasoning
- Module 2: Bayesian inference and prediction
Afternoon session (1-4pm) will focus on incorporating Bayesian elements in intermediate and advanced undergraduate courses
- Module 3: Bayesian regression models
- Module 4: Bayesian hierarchical models