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The study aims to examine how auditors specify prior distributions in Bayesian statistics and their impact on audit conclusions.

Assessing Prior Distributions for Applying Bayesian Statistics in Auditing.

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The study aims to examine how auditors specify prior distributions in Bayesian statistics and their impact on audit conclusions.
Analyzed how auditors construct prior distributions based on available information.
Evaluated the concentration of probability in prior distributions regarding error amounts.
Investigated inconsistencies in auditors’ methods of specifying prior distributions.
Most prior distributions concentrated probability on small errors but showed considerable variability.
Substantial inconsistencies were found in specifying prior distributions among auditors.
Some prior distributions may not accurately reflect auditors' beliefs about the audit populations.

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Auditors assess prior distributions for Bayesian statistics, indicating variability and caution in outcomes.

John C. Corless (1972) studied this question.

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