TY - JOUR

T1 - A Bayesian Solution for a Statistical Auditing Problem

AU - Meeden, Glen

PY - 2003/9

Y1 - 2003/9

N2 - 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.

AB - 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.

KW - Dichotomous variable

KW - Finite population sampling

KW - Noninformative Bayes

KW - Statistical auditing

UR - http://www.scopus.com/inward/record.url?scp=0242679441&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0242679441&partnerID=8YFLogxK

U2 - 10.1198/016214503000000648

DO - 10.1198/016214503000000648

M3 - Article

AN - SCOPUS:0242679441

SN - 0162-1459

VL - 98

SP - 735

EP - 740

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

IS - 463

ER -