An IS auditor should use statistical sampling when which of the following conditions is met?

Statistical sampling is a method that utilizes the principles of probability to provide a quantifiable estimation of the characteristics of a population based on a sample. It is particularly useful in auditing because it allows auditors to draw conclusions about a larger group from a smaller subset while ensuring that conclusions can be supported with a known level of confidence.

The condition that the probability of error must be objectively quantified aligns with the essence of statistical sampling, which relies on statistical theory to estimate the likelihood of various outcomes or errors. This quantification is essential because it defines the level of assurance the auditor has in the results derived from the sample. By knowing the probability of error, the auditor can determine whether the controls are effective or whether further investigation is needed.

This contrasts with other conditions. For example, the desire to avoid sampling risk does not call for the use of statistical sampling, as sampling risk is an inherent aspect of any sampling method—statistical sampling merely quantifies it. Similarly, the unavailability of generalized audit software does not dictate the use of statistical sampling; rather, the choice of sampling method depends more on the audit objectives and context. Lastly, the inability to determine a tolerable error rate does not provide a rationale for using statistical sampling, as the effectiveness of statistical sampling