What question did this study set out to answer?

The primary aim is to introduce a quasi-Bayesian model for estimating the expected total error in dollar unit sampling.

A Quasi-Bayesian Audit Risk Model for Dollar Unit Sampling.

View Full Paper

Ask AI

Bookmark

Authors

This analysis demonstrates a quasi-bayesian model assessing error in dollar unit sampling, indicating its utility in diverse scenarios.

The primary aim is to introduce a quasi-Bayesian model for estimating the expected total error in dollar unit sampling.
Developed a model for discrete posterior probability distribution on error estimates.
Applied the model to any sample size and error types (overstatements and understatements).
Demonstrated comparisons with multinomial upper bounds.
The model can utilize existing data on errors in the population.
Findings suggest the proposed model is effective for evaluating dollar unit samples even without informative priors.

John H. McCray (1984) studied this question.

View Full Paper

Ask AI

Bookmark