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    Field Data on Accounting Error Rates and Audit Sampling
    research summary posted February 19, 2015 by Jennifer M Mueller-Phillips, last edited July 20, 2015, tagged 08.0 Auditing Procedures – Nature, Timing and Extent, 08.02 Sample Selection – use of statistical sampling, 08.04 Auditors’ Professional Skepticism, 09.0 Auditor Judgment, 09.08 Evaluation of Errors – Statistical and Non-statistical 
    Field Data on Accounting Error Rates and Audit Sampling
    Practical Implications:

    This study provides several important practice implications. First, prior research on audit sampling that relied on the assumption of relatively large error rates may not provide useful guidance for post-SOX audit sampling populations. Second, auditing educators, regulators, and standard setters benefit from an updated understanding of how auditors apply audit sampling guidance in auditing standards when using audit sampling in the field. For example, knowing the relatively high compliance (compared with prior periods) with requirements in auditing standards should impact the way audit sampling is taught in universities and firm trainings, how peer and federal inspectors address audit sampling issues, as well as the need for further clarity of auditing standards. Auditors also benefit as they consider the sampling techniques and input assumptions that will produce the most effective and efficient sampling plans. Specifically, an important implication of our study is related to the impact of standardized sampling templates. The firm in this study mandated the use of such templates, which contributed to levels of explicit consideration of error projection, sufficiency of sample sizes, and of sampling risk in planning and evaluating sample testing.

    For more information on this study, please contact Steve Glover.


    Durney, M., R. J. Elder, and S. M. Glover. 2014. Field data on accounting error rates and audit sampling. Auditing: A Journal of Practice and Theory 33 (2): 79-110

    Sampling, error rates, error projection, sampling risk
    Purpose of the Study:

    Prior research has examined error characteristics of accounting populations. Many studies investigating audit sampling techniques rely on assumptions concerning the error characteristics of accounting populations. Prior research studies examining auditor performance when using audit sampling have reported:

    • Decreasing sample sizes for tests of details.
    • Auditors frequently fail to project sample errors.
    • Auditors do not consider sampling risk when projecting sample errors.

    These studies involve data from periods preceding the events resulting in the Sarbanes–Oxley Act (hereafter, SOX). Much has happened since SOX, including a renewed focus on audit quality, new auditing and accounting standards, and the creation of the PCAOB. Using proprietary post-SOX data from a large accounting firm, the authors report on:

    • Error rates in populations subject to audit sampling.
    • Auditor compliance with auditing standards with regards to error projection, sample size, and consideration of sampling risk.
    Design/Method/ Approach:

    Data for the study is comprised of the results of 160 different sampling applications from a large auditing firm in 2005 and 2006. The sampling applications were applied across a range of financial statement accounts including accounts receivable, inventory, loans, expenses, plant additions, and revenues. All the tests were substantive tests of details and meant to be representative of the population.


    The authors find the following:

    • Error rates in populations subject to audit sampling are significantly lower in magnitude and frequency than researchers have traditionally assumed.
    • Significantly larger sample sizes and higher error projection rates than reported in previous studies using pre-SOX data.
    • Explicit consideration of sampling risk by auditors.
    Auditing Procedures - Nature - Timing and Extent, Auditor Judgment
    Conclusions Based on Samples, Evaluation of Errors - Statistical and Non-statistical, Sample Selection – use of statistical sampling