A Bayesian Redesign of the First Probability/Statistics Course

Abstract

The traditional calculus-based introduction to statistical inference consists of a semester of probability followed by a semester of frequentist inference. Cobb (2015) challenges the statistical education community to rethink the undergraduate statistics curriculum. In particular, he suggests that we should focus on two goals: making fundamental concepts accessible and minimizing prerequisites to research. Using five underlying principles of Cobb, we describe a new calculus-based introduction to statistics based on simulation-based Bayesian computation.