Designing Tests/Sampling

60.6 – Designing Tests/Sampling (Rev. 60, Issued: 11-26-04, Effective: 10-01-04, Implementation: 01-24-05) Design such tests as are necessary to accomplish your audit objectives. Your tests must aid you in reaching conclusions necessary to complete the audit. Use sampling when this would be more efficient in testing the universe of transactions, entries, or statistical data within an area of consideration. Sampling is the application of an audit procedure to less than 100 percent of the items within an account balance, class of transactions, or statistics (e.g., count of interns/residents) to evaluate some characteristic of the such balance, class, or statistics. On the basis of facts known to you, decide if all transactions, balances, or statistics that pertain to the issue/area being tested need to be reviewed in order to obtain sufficient evidence. In most cases, an auditor will test at a level less than 100 percent. There are two general sampling approaches, nonstatistical and statistical. Either approach, when properly applied, can provide sufficient evidential data related to the design and size of an audit sample, among other factors. A nonstatistical sample may support acceptance of findings, but findings must be scientifically established to support adjustments. Some degree of uncertainty is inherent in applying audit procedures and is referred to as ultimate risk. Ultimate risk includes uncertainties due both to sampling and other factors. Sampling risk arises from the possibility that when a compliance or a substantive test is restricted to a sample, the auditor's conclusions may be different had the test been applied in the same way to all items in the account balance, class of transactions, or statistics. If you use a sample to test certain issues scoped for audit, you must include a description of the sampling technique, all parameters used to select the sample, and confidence level in the audit working papers. A. Planning Samples Planning an audit involves a strategy for selecting appropriate sample(s). When planning a particular sample, consider: • The relationship of the sample to the audit objective (e.g., Medicare policies for determining the GME and IME FTE counts of residents differ and these differences must be considered in the decision whether it is feasible to use one sample to test the FTE counts for both purposes); • Preliminary estimates of materiality levels; • The allowable risk of incorrect acceptance; and • Characteristics of the population, i.e., the items comprising the universe. B. Selecting a Sampling Approach Because either nonstatistical or statistical sampling can provide sufficient evidence, choose between them after considering their relative cost and effectiveness. Statistical sampling helps to: • Design an efficient sample; • Measure the sufficiency of the evidential matter obtained; and • Evaluate the results. By using statistical theory, quantify sampling risk in limiting it to an acceptable level. Statistical sampling involves additional costs of designing individual samples to meet the statistical requirements and selecting items to be examined. Where the audit objective would be best accomplished by stratifying the universe/population into high and low strata (e.g., where Medicare bad debts are being tested), use your judgment in designating the threshold for this stratification. Once determined, review all the items in the high strata population and use statistical or nonstatistical sampling to test the low strata. C. Sampling Risk In performing substantive tests of details, consider: • The risk of incorrect acceptance that the sample supports the conclusion that the items are not materially misstated when they are; and • The risk of incorrect rejection that the sample supports the conclusion that the items are materially misstated when they are not. D. Using the Test Results If the results of testing your sample that was selected using a nonstatistical method indicate probable errors in the universe of transactions, entries, or statistics, document your decision to expand the sample or redesign the sample using a statistical method. If the results of testing your sample that was selected using a statistical method indicate probable errors in the universe, document your decision to project the error to the universe/population. If your adjustment pertains only to the error(s) that was identified, you must document the reason for not considering the effect of the error(s) on the universe.