Integrating statistical and nonstatistical audit evidence using belief functions: A case of variable sampling

Rajendra P. Srivastava, Glenn R. Shafer

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

The main purpose of this article is to show how one can integrate statistical and nonstatistical items of evidence in the belief function framework. First, we use the properties of consonant belief functions to define the belief that the true mean of a variable lies in a given interval when a statistical test is performed for the variable. Second, we use the above definition to determine the sample size for a statistical test when a desired level of belief is needed from the sample. Third, we determine the level of belief that the true mean lies in a given interval when a statistical test yields certain values for the sample mean and the standard deviation of the mean for the variable. Finally, we use the auditing situation to illustrate the process of integrating statistical and nonstatistical items evidence. © 1994 John Wiley & Sons, Inc.

Original languageEnglish (US)
Pages (from-to)519-539
Number of pages21
JournalInternational Journal of Intelligent Systems
Volume9
Issue number6
DOIs
StatePublished - 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

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