Statistical sampling in federal tax filings.

• Author: Batcher, Mary

Statistical sampling is pervasive in daily life. A physician drawing a small amount of blood for testing or someone tasting a small bite of a new food is an example of sampling. These methods can provide valuable information so long as the sample is representative and well-mixed. The physician does not need to drain all the blood out of a body because blood is well-mixed, so a small sample is representative. When tasting food, samples are less certain. If a soup is stirred, it is generally well-mixed and the small taste is representative. But if it is not well-mixed, the taste could be atypical. Thus, a good sample is one that properly reflects the variations that occur in the whole "population" or "universe."

Sampling is increasingly relied on by government regulators including the IRS, the Federal Communications Commission, and the Department of Health and Human Services. Numerous tax agencies--state, federal, and foreign--have published guidelines for taxpayer use of sampling for estimating values that are reported or claimed on tax returns. The AICPA has published guidelines including Statement on Auditing Standards No. 39, Audit Sampling.

Sampling Pros and Cons

Advantages of sampling include:

1. The ability to reasonably assess accuracy or quantify an amount using fewer resources.

2. Less disruption of normal business operations with fewer documentation requests.

3. The ability to thoroughly review fewer documents rather than make a cursory review of all of them, leading to a more accurate result. Extrapolating results from a sample of thoroughly reviewed and corrected records is often more accurate than using the whole database subjected to only high-level checks or minimal review.

4. Increasing regulatory and judicial acceptance.

   Disadvantages may include:

1. Inaccuracies stemming from random chance, unrepresentative samples, or an ill-conceived approach.

2. Potential mistrust of the value of sample results by people unfamiliar with sampling.

3. Failure to recognize the limitations of a sample and, as a result, overextending the sample results.

   Statistical and Judgment Sampling

   The basic means of sample selection give rise to two forms of samples: judgment and statistical (or probability) samples. With judgment samples, a knowledgeable person chooses representative or illustrative test cases or, sometimes, problematic cases. In either situation, human judgment is used to choose the items to include in the sample. Haphazard sampling, e.g...