What question did this study set out to answer?

This article aims to evaluate the relevance and differences between positive and negative hypothesis testing approaches in auditing.

June 15, 2026

A Reevaluation of the Positive Testing Approach in Auditing.

Key Points

This article aims to evaluate the relevance and differences between positive and negative hypothesis testing approaches in auditing.
Discusses statistical sampling literature on hypothesis testing approaches in auditing.
Analyzes confidence levels and risks associated with both approaches.
Compares implications of each method on aggregate error during audits.
Highlights that the positive testing approach aligns confidence level with alpha risk, while the negative approach aligns it with beta risk.
Identifies that under high aggregate error scenarios, the negative approach increases beta risk compared to the positive approach.

Abstract

Abstract The article informs that the majority of the statistical sampling literature suggests that both the positive and negative hypotheses testing approaches are equally relevant in auditing. The difficulty noted in two is compounded by the fact that the positive approach is inconsistent with the negative approach that is always used in attribute sampling with compliance testing, and in dollar unit sampling. Thus, the essential difference between the two hypothesis testing approaches is that under the positive testing approach, confidence level equals one minus alpha risk while under the negative approach, confidence level equals one minus beta risk (e.g., see Roberts 1974, p. 54 and Duke et al. They predict that when aggregate error is large, due to large overstatement errors, the negative testing approach (what they refer to as the SAP 54 decision rule) results in higher ex post beta risk than the positive approach (what they refer to as the E& R decision rule).

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