Although audit sampling is a common procedure, relatively little is known about the sampling practices of auditors in public accounting, industry, and government. This study surveyed practicing auditors to determine how they: (1) planned sample sizes, (2) selected sample items, and (3) evaluated sample outcomes. Respondents also provided data on the training received, debiasing techniques employed when using nonstatistical (judgmental) methods, and literature sources relied on to provide guidance regarding sampling matters. Respondents in all areas of practice reported that a majority of audit sampling applications rely on nonstatistical methods for sample planning, selection, and evaluation. Despite the heavy reliance on nonstatistical methods, less than 10 percent of respondents reported receiving training in debiasing techniques, and no respondents reported using these techniques. Among statistical methods dollar-unit sampling is the most frequently employed technique. All respondents reported reliance on employer guidelines, and most reported reliance on sampling standards promulgated by the American Institute of Certified Public Accountants.

Over 40 years ago both Deming (1954) and Arkin (1957) expressed concerns that the composition of samples chosen through haphazard selection may be unrepresentative due to the presence of unintended selection biases. To mitigate this problem some experts in the field of audit sampling recommend increasing sample sizes by up to 100 percent when utilizing haphazard selection. To examine the effectiveness of this recommendation 142 participants selected haphazard samples from two populations. The compositions of these samples were then analyzed to determine if certain population elements were overrepresented, and if the extent of overrepresentation declined as sample size increased. Analyses disclosed that certain population elements were overrepresented in the samples. Also, increasing sample size produced no statistically significant change in the composition of samples from one population, while in the second population increasing the sample size produced a statistically significant but minor reduction in overrepresentation. These results suggest that individuals may be incapable of complying with audit guidelines that haphazard sample selections be made without regard to the observable physical features of population elements and cast doubt on the effectiveness of using larger sample sizes to mitigate the problem. Given these findings, standard-setting bodies should reconsider the conditions under which haphazard sampling is sanctioned as a reliable audit tool.

Haphazard sampling is a nonstatistical technique used by auditors to simulate a variety of random sampling techniques when testing the error status of accounting populations. In this study, we compare the properties of haphazard samples selected from control listings with the properties of simple random samples. We hypothesize that control listing entries exhibit salience values that result from the effort required to locate entries and the visual properties of entries. We further hypothesize these salience values influence sample selections and result in sample properties that are different from those of simple random samples. To test these hypotheses, we examine the properties of haphazard samples selected by three participant groups. In each group, sample properties differ from those of simple random sampling and include a lack of independence across sample selections and biased sample inclusion probabilities. We also develop models showing how biased sample inclusion probabilities influence error projections and discuss the estimation consequences of these biases. Data Availability: For information about data availability, please contact the first author.

SUMMARY:This article summarizes our recent study, ''Haphazard Sampling: Selection Biases Induced by Control Listing Properties and the Estimation Consequences of These Biases' ' (Hall et al. 2012). Haphazard sampling is a nonstatistical technique used by auditors to simulate random sampling when testing the error status of accounting populations. Our study compared the properties of haphazard samples selected from control listings with the properties of random samples. We hypothesized that haphazard samples differ from random samples because the haphazard selection process is influenced by: (1) auditor behaviors intended to minimize sample selection effort and to ensure a diversified sample composition, and (2) variations in the appearance of control listing entries. Results from three experiments confirmed multiple differences between haphazard samples and random samples, and suggest that haphazard sampling may not be a reliable substitute for random sampling. In the absence of effective remediation procedures, continued use of haphazard sampling may expose auditors to additional audit, legal, and regulatory risk.

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