What is Non-Statistical Sampling?

Non-statistical sampling is the selection of a test group that is based on the examiner's judgment, rather than a formal statistical method. For example, an examiner could use his own judgment to determine one or more of the following:

The sample size
The items selected for the test group
How the results are evaluated

To reduce the amount of variability in a non-statistically determined sample size, an examiner usually refers to a table that sets forth the approximate sizes to be used. For example, a low-risk situation may call for the selection of 25 records, while a high-risk situation might mandate the selection of 100 records.

When using a non-statistical approach to select the items for a test group, the examiner should not introduce too much bias into the selections. For example, do not lean too heavily on supplier invoices where the invoice amount exceeds $10,000 and the name of the supplier begins with a "P". Instead, the selection should come as close as possible to representing the entire population of records.

When to Use Non-Statistical Sampling

It can make sense to use non-statistical sampling when the population size is very small. In this case, it is not efficient to spend the extra time to set up a statistical sample. This approach is also useful in areas where specific records contain sensitive information, and so must be examined. For example, an examiner might want to select the invoices of specific law firms, because these firms deal with environmental obligations, which may involve substantial liabilities.

Disadvantages of Non-Statistical Sampling

The main concern with non-statistical sampling is that not every item in the underlying population has the same probability of being selected, resulting in a skewed outcome. If there is a substantial amount of bias in the selection process, then the characteristics of the sample might differ substantially from the characteristics of the underling population.