Jingchen (Monika) Hu (Vassar College) & Kevin Ross (Cal Poly)
There are many reasons why aspects of Bayesian statistical analysis should be introduced in the undergraduate curriculum, in introductory through advanced levels. In particular, Bayesian methods are becoming increasingly popular in scientific applications. Statistics educators should evolve curricula to include Bayesian statistical analysis in order to nurture new generations of citizen statisticians. However, statistics educators might be uncertain how or why to introduce Bayesian ideas, especially if they do not have much experience with Bayesian statistics.
This workshop provides resources and support for statistics educators to incorporate aspects of Bayesian statistics in their teaching. Through examples and hands-on practice in breakout room sessions, participants will learn how to design modules for teaching concepts and applications of Bayesian statistical analysis in both introductory and advanced courses. We will also discuss designing introductory and advanced statistics courses from a Bayesian perspective.
No prior experience with Bayesian statistics is required. Participants should have access to a computer, and R will be used during parts of the workshop. Participants are encouraged to bring an existing ("frequentist") activity or example to investigate from a Bayesian perspective during breakout sessions.
Workshop materials can be found here: https://github.com/monika76five/USCOTS2021_workshop