Teaching statistical reasoning in business: Understanding type II error through COVID-19 testing

Hypothesis testing is a fundamental topic in business statistics, preparing future professionals with decision-making skills. However, its probabilistic nature and complex concepts, including sampling distributions, significance levels, Type I errors, Type II errors, and p-values, make it challenging to teach. Type I errors often receive more focus, while Type II errors are frequently overlooked despite their potential for serious business implications. To address this, we use COVID-19 testing as a relatable, high-stakes example of the risks posed by Type II errors. Pre- and post-treatment surveys in business statistics courses showed this real-world example significantly improved students' understanding of Type II errors by connecting abstract concepts to practical decisions.