In attribute sampling, what is the relationship between expected error rate and sample size?
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A. B. C. D.C.
Attribute sampling is a statistical method used in auditing to determine the reliability of a population of data. In attribute sampling, the auditor examines a sample of items from a larger population to determine the percentage of items in the population that possess a specific characteristic or attribute.
The expected error rate refers to the percentage of items in the population that the auditor expects to contain an error. The error rate can be determined based on prior audit experience or the auditor's knowledge of the system being audited.
The sample size, on the other hand, refers to the number of items selected for examination from the population. The sample size is important because it affects the precision and reliability of the audit results.
In attribute sampling, the relationship between the expected error rate and the sample size is inverse. This means that the greater the expected error rate, the greater the sample size needed to achieve the desired level of precision and reliability in the audit results. Conversely, the smaller the expected error rate, the smaller the sample size needed.
The correct answer, therefore, is (C) The greater the expected error rate, the greater the sample size. Option (A) is incorrect because the expected error rate does affect the sample size. Option (B) is incorrect because the greater the expected error rate, the larger the sample size required. Option (D) is incorrect because increasing the sample size does not necessarily result in a lower expected error rate.