Final answer:
Depending on the sample size chosen, the auditor may achieve the desired precision despite not using statistical concepts to determine it. Random selection adds representativeness, but evaluation must be cautious. Differentiation between sampling errors and nonsampling errors is critical.
Step-by-step explanation:
If the sample size in a test of controls is not determined by using statistical concepts, but is chosen based on random selection procedures, the most accurate interpretation is that depending on the size of the sample chosen, the auditor may actually achieve desired precision. This outcome occurs because even without the application of statistical techniques to determine the sample size, the randomness of the selection helps in ensuring that the sample is representative of the population, which is a foundational element of good sampling practices.
Moreover, the rules of thumb on sufficient sample sizes suggest that, under certain assumptions, a larger sample size can enhance the reliability of the results. However, the absence of statistical sizing means that the auditor must remain cautious in extrapolating the results to the entire population. They must meticulously evaluate the outcomes, which might include using the principles of discovery sampling or other forms of analysis to validate their findings.
It is also necessary to differentiate between sampling errors and nonsampling errors. A sampling error occurs due to the inherent process of sampling, such as a sample that is not large enough, while nonsampling errors arise from factors unrelated to the sampling process. By following random selection procedures, the auditor avoids systematic selection biases, which minimizes certain types of nonsampling errors.