Bayesian methodology continues to be widely used in statistical applications. As a result, it is
increasingly important to introduce students to Bayesian thinking at early stages in their
mathematics and statistics education. While many students in upper level probability courses can
recite the differences in the Frequentist and Bayesian inferential paradigms, these students often
struggle using Bayesian methods when conducting data analysis. Specifically, students tend to
struggle translating subjective belief to the specification of a prior distribution and the
incorporation of uncertainty in the Bayesian inferential approach. The purpose of this paper is to
present a hands-on activity involving the Beta-Binomial model to facilitate an intuitive
understanding of the Bayesian approach through subjective problem formulation which lies at
the heart of Bayesian statistics.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education