Introducing Frequentist and Bayesian Methods in Parallel in an Undergraduate Economics Statistics Course

Oregon Convention Center 

Economic statistics courses prepare students to analyze data using exclusively the frequentist method, despite the increasing use of the Bayesian approach in economics applications. Inspired by Rittle-Johnson and Star's evidence (2009, 2011, 2020) on the educational benefits of comparative learning in mathematics, this paper utilizes the structure of an existing undergraduate economic statistics course, which emphasizes the frequentist approach, to introduce the Bayesian approach in parallel. Comparisons were made using the Beta-Binomial model for proportions and the Normal-Normal model for means. Applied exercises were conducted using R Studio and the bayesrules package. The main purpose of this teaching approach is not only to familiarize students with both methodologies but also to enhance their understanding of concepts that are often misunderstood in the frequentist framework, such as p-values, confidence intervals, and the implicit assumptions used to derive the distribution of estimators. I also present reflections on the benefits and challenges I encountered during my first implementation of this teaching format.