Monetary unit sampling: a belief-function implementation for audit and accounting applications

Abstract Audit procedures may be planned and audit evidence evaluated using monetary unit sampling (MUS) techniques within the context of the Dempster–Shafer theory of belief functions. This article shows: (1) how to determine an appropriate sample size for MUS in order to obtain a desired degree of belief that the upper bound for misstatements lies within a given interval; and (2) what level of belief in a specified interval is obtained given a sample result. The results are consistent with the view that a specified level of belief in an interval is semantically a stronger claim than the same numerical level of probability. The paper describes two variants of MUS in both probability and belief-function forms, emphasizing the systematic similarities and the numerical differences between the two frameworks. The results, based on the Poisson distribution, extend results already available for mean-per-unit variables sampling, and may readily be developed to give similar results for the binomial distribution.

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