The Importance of Statistical Sampling in Auditing
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Question
Which of the following is the MOST important reason to use statistical sampling?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.C.
Statistical sampling is a technique used to select a representative sample from a larger population in order to draw conclusions about the population as a whole. This technique is commonly used in auditing and other fields where it is impractical or impossible to examine every item in a population.
Out of the given options, the MOST important reason to use statistical sampling is A. The results are more defensible. This is because statistical sampling is a structured approach that uses mathematical principles to select a sample that is representative of the larger population. This reduces the risk of bias and provides a basis for making objective conclusions.
The use of statistical sampling also allows auditors to quantify the level of risk associated with a particular area or population being tested. By selecting a sample that is statistically significant, auditors can estimate the level of error or noncompliance in the population as a whole with a certain degree of confidence.
While options B and C are also benefits of using statistical sampling, they are not as important as the defensibility of the results. While statistical sampling does not guarantee that all relevant cases will be covered, it does provide a reasonable basis for estimating the level of error or noncompliance in the population as a whole. Similarly, while statistical sampling can reduce the time required for testing, this is a secondary benefit to the increased defensibility of the results.
Option D, "The results can reduce error rates," is not as strong a reason to use statistical sampling as option A. While statistical sampling can reduce error rates, the more important benefit is the defensibility of the results. In addition, statistical sampling cannot completely eliminate the risk of errors, as there is always a margin of error associated with any statistical sample.