PRACTITIONER'S GUIDE TO AUDIT SAMPLING

By Dan M. Guy, Douglas R. Carmichael, O. Ray Whittington

John Wiley & Sons, Inc. $65, 162pp, excluding appendices. ISBN: 0-471-24635-2

Reviewed by Vincent J. Love, CPA, Kramer and Love

The authors, all well known and respected educators and auditing theorists, set out to reduce the gap between books that give only introductory coverage to audit sampling and the basic level of professional guidance required to cope with audit sampling applications in practice. They were successful. This text, which covers both statistical and nonstatistical sampling, will refresh the practitioner's knowledge of sampling techniques and serve as a guide to the practical implementation of sampling in audits and other similar processes.

For a book primarily devoted to the understanding and use of statistical sampling techniques, it is surprisingly easy to read. Only occasionally do the authors get bogged down in the underlying mathematical equations. Attribute and variable sampling methods are addressed. Cautions concerning the application of each method and the proper situation for its use are adequately covered. Additionally, the authors reference other authoritative literature to create a mosaic encompassing the entire gamut of the standards related to audit testing.

One point driven home and beautifully illustrated by the authors is the importance of professional judgment in the use of statistical methods to determine and interpret statistically based samples and results. The authors give the reader relevant and practical examples of judgments that are made--qualitative judgments are given greater significance than quantitative methods in interpreting sampling results.

The use of attribute sampling in audit planning and testing internal control is addressed with useful, practical examples to aid the reader's understanding. Next, variable sampling and its use in the substantive testing of account balances is explained and illustrated. Throughout the text, advice is given on when and how to use these statistical sampling techniques during an audit engagement.

The most difficult chapter to follow, because of the complicated theory and use of statistical equations, is chapter 4, Using Variable Sampling for Accounting Estimation. However, the reader can take solace in the fact that an independent auditor rarely uses this type of sampling. The independent auditor most often deals with verifying management's representation concerning account balances and not estimating the amount to be recorded in a client's books and records.

Positioned at the back of the main text and the shortest of the chapters, the chapter on the use of nonstatistical audit sampling is jam-packed with concepts, ideas, and suggestions relating to risk assessment and nonstatistical sample selection and interpretation. This chapter alone is worth the price of the book. Practitioners who do not use statistical sampling techniques in their audit engagements should definitely read this chapter and consider the authors' approach and suggested procedures.

Each chapter begins with a synopsis of what will be covered and ends with a summary of what was covered and a glossary of the terms introduced in the chapter. The book includes four appendices--the first illustrates worksheets that can be used in audit testing; the second lists equations (for the stout-hearted); the third is a reprint of SAS No. 39 (AU 350); and the last is a copy of the interpretations of AU 350.

The book includes a 3.5-inch floppy disk of templates for audit testing ("AuditAid") for use with Microsoft Excel for Windows version 5.0 or higher--tough luck for Mac users like this reviewer. A colleague of mine feels the these templates could be improved through the greater use of macros.