The Bayesian Approach to Audit Evidence: Quantifying Statistical Evidence Using the Bayes Factor
论证了审计中常用的频率派统计方法无法提供审计标准所需的统计证据，并介绍贝叶斯推断作为替代方案，展示贝叶斯因子如何帮助审计师量化证据强度。
SUMMARY Statistical methods play an important role in auditors’ analyses of their clients’ data. A key component of the statistical approach to auditing is assessing the strength of evidence for or against a hypothesis. We argue that the frequentist statistical methods often used by auditors cannot provide the statistical evidence that audit standards advocate. In this article, we discuss an alternative approach that can provide this evidence: Bayesian inference. First, we explore the philosophical differences between frequentist and Bayesian inference. Second, we discuss misconceptions in the interpretation of frequentist statistical evidence. Finally, we show (as an alternative to the frequentist p-value) how the Bayes factor allows the auditor to obtain and interpret statistical evidence in line with audit standards. Thus, we contribute to audit theory and practice by showing how Bayesian inference can quantify audit evidence. Data Availability: The data supporting the findings in this article are available in the OSF repository at https://doi.org/10.17605/OSF.IO/WTN9G.1