Decision-Theoretic Hypothesis Testing: A Primer With R Package OptSig

Abstract

This article is a primer for a decision-theoretic approach to hypothesis testing for students and teachers of basic statistics. Using three examples at an introductory level, this article demonstrates how decision-theoretic hypothesis testing can be taught to the students of basic statistics. It also demonstrates that students and researchers can make more sensible and unambiguous decisions under uncertainty by employing this particular approach. The examples are illustrated using R and its package “OptSig.”

KEYWORDS:

• Effect size
• Expected loss
• Optimal significance level
• Power analysis

Acknowledgments

This article is based on the presentation the author made at the Australian Teaching Economics Conference held in Melbourne in July 2019. The author would like to thank In Choi, David Johnstone, Jenny Lye, Steven Parker, and Yuji Tamura for their comments and suggestions. Constructive comments from the reviewers and editors are also gratefully acknowledged.