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
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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 -