Statistical Sampling for Fraud Detection

A

The statement "Statistical sampling enables the examiner to predict the occurrence rate for the population and therefore determine with some accuracy the error rate, or the potential for fraud" is generally true.

Statistical sampling is a technique used by fraud examiners to select a subset of a population for examination when it is not feasible or practical to examine the entire population. In statistical sampling, a sample is drawn from the population, and the results from the sample are then used to make inferences about the population as a whole.

By using statistical sampling, an examiner can estimate the occurrence rate of certain attributes in the population, such as the error rate or the potential for fraud. This can be done by calculating the point estimate, which is the best estimate of the occurrence rate, as well as the confidence interval, which is a range of values within which the true occurrence rate is likely to fall.

The level of accuracy of the estimate depends on several factors, including the sample size, the method of sampling used, and the variability of the attribute being measured. However, statistical sampling provides a structured approach for making reliable inferences about the population from a sample.

Therefore, the statement "Statistical sampling enables the examiner to predict the occurrence rate for the population and therefore determine with some accuracy the error rate, or the potential for fraud" is generally true. However, it is important to note that statistical sampling is just one tool in the fraud examiner's toolbox and should be used in conjunction with other techniques and tools to obtain a complete understanding of the situation.