Embracing Bayesian Inference for Enhanced Audit Evidence

In a thought-provoking article published in AUDITING: A Journal of Practice & Theory, Koen Derks, Jacques de Swart, Eric-Jan Wagenmakers, and Ruud Wetzels advocate for the adoption of Bayesian inference in auditing. The paper highlights the limitations of frequentist statistical methods, commonly used by auditors, in providing the robust statistical evidence required by audit standards.

The authors delve into the philosophical differences between frequentist and Bayesian approaches, addressing common misconceptions about frequentist evidence. They introduce the Bayes factor as a superior alternative to the frequentist p-value, demonstrating how it enables auditors to quantify and interpret evidence more effectively.

By showcasing the practical application of Bayesian inference, this article contributes significantly to audit theory and practice, offering a compelling case for modernizing statistical methodologies in the audit profession.