A Bayesian Solution for a Statistical Auditing Problem

Glen Meeden

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Auditors often consider a stratified finite population where each unit is classified as either acceptable or in error. Based on a random sample, the auditor may be required to give an upper confidence bound for the number of units in the population that are in error. In other cases the auditor may need to give a p value for the hypothesis that at least 5% of the units in the population are in error. Frequentist methods for these problems are not straightforward and can be difficult to compute. Here we give a noninformative Bayesian solution for these problems. This approach is easy to implement and is shown to have good frequentist properties.

Original languageEnglish (US)
Pages (from-to)735-740
Number of pages6
JournalJournal of the American Statistical Association
Issue number463
StatePublished - Sep 1 2003


  • Dichotomous variable
  • Finite population sampling
  • Noninformative Bayes
  • Statistical auditing

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