Research Summary 22: Haphazard Sampling and Selection Bias

verybody has a favorite color and season—preferences that seem innate, always defying reason. Auditors are no different when it comes to haphazard sampling, a process in which—ideally—they choose samples without regard to size, shape, location or other physical characteristics. Experts have expressed concern about bias in such sampling and, as an antidote, have prescribed an increase in sample size by 100% to mitigate auditors’ “subconscious” tendencies to be “picky.”

Our study investigated whether increasing sample size was an effective technique to reduce selection bias. We asked 142 undergraduate accounting seniors to use haphazard sampling in selecting from two simulated populations—one of items in inventory bins, another of vouchers. We analyzed the composition of the samples to determine whether certain items were overrepresented and whether the extent of overrepresentation declined as sample size increased. Consistent with previous research, we found size and location influenced haphazard selections. Increasing sample size did not produce any material change in the samples’ composition. This finding showed that more was not necessarily better—at least for haphazard sampling—and bias seemed to prevail.

How deep do auditors’ biases run? Although we found bias in samples selected physically, we suspected it also might have played a part in choosing items from a list (for example, picking accounts receivable from a trial balance), an important avenue for future research.

Given our findings, auditors should reevaluate their heavy reliance on haphazard sampling. For critical applications, they should use random selection techniques, which skirt the problem of sampling bias. Standard-setting bodies, such as the ASB and IFAC, should reconsider conditions under which they sanction haphazard sampling as a reliable audit tool.

For the full text of the research paper, see “The Effectiveness of Sample Size to Mitigate the Influence of Population Characteristics in Haphazard Sampling,” Auditing: A Journal of Practice & Theory, March 2001, vol. 20, no. 1.

THOMAS W. HALL, CPA, PhD, is professor and chairman, Department of Accounting, University of Texas at Arlington. His e-mail address is wave@uta.edu . TERRI L. HERRON, CPA, PhD, is a certified information systems auditor and assistant professor, Department of Accounting and Finance, University of Montana, Missoula. BETHANE JO PIERCE, CPA, PhD, is associate professor and TERRY J. WITT, CPA, is professor emeritus, Department of Accounting, University of Texas at Arlington.