Original Question: (Do not reply to this one)
How are the desired confidence level, the tolerable misstatement, and the expected misstatement related to sample size?
Student Discussions:
Reply to each student posts by commenting about their posts and building on the subject (About 100 words each) APA reference.
APA reference.
1-Sidnee Yaeger
Monetary-unit sampling (MUS) is “based on attribute-sampling theory modified to express a monetary conclusion rather than a rate of occurrence” (Messier, Glover, & Prawitt, 2017).When judgement is required to regulate the suitable values for the inputs used to compute to MUS sample size, four factors must be considered: desired confidence level, tolerable misstatements, expected misstatements, and population size (Messier, Glover, & Prawitt, XXXXXXXXXXDesired confidence level and sample size have a direct relationship. To have a larger amount of confidence, more work is essential, which leads to an increase in sample size.Therefore, confidence level and incorrect acceptance are complements. If an auditor has a certain desire to be correct, they must be willing to be okay being incorrect the remainder of the time. For example, if an auditor has a 95 percent confidence, they must be okay with being incorrect 5 percent of the time. Secondly, tolerable misstatements and sample size are opposites or act inversely to one another. As the tolerable misstatements increase or decrease, the sample size goes in the opposite direction (Messier, Glover, & Prawitt, 2017).If the tolerable misstatements are low, sample size needs to be larger to increase the tests. Third, expected misstatement and sample size has a direct relationship. The expected misstatement is the dollar value that appears in the population.The larger amount of expected misstatements, the larger the sample size. The auditor needs more precise information, causing a larger sample size, to determine the expectation (Messier, Glover, & Prawitt, 2017).
References:
Messier, W. F., Glover, S. M., & Prawitt, D. F XXXXXXXXXXAuditing & Assurance Services: A Systematic Approach (10th ed.). New York: McGraw-Hill/Irwin. ISBN: XXXXXXXXXX
2-Maurice Naylon
In conducting audit sampling, three interrelated inputs represent the key information needed to determine appropriate sample size: “(1) desired level of assurance in the results of the sample (or confidence level), (2) acceptable defect rate (or tolerable error), and (3) historical defect rate (or expected error)” (Messier et al, 2017, p. 267).By examining each of these factors, the audit team can determine an appropriate sample size. Specifically, auditors first determine their necessary confidence level.This metric “is the complement of sampling risk,” that is, it “represents the probability that a given interval includes the true, but unknown, measure of the characteristic of interest,” and this level is directly related to sample size: “the larger the sample, the higher the confidence level and the lower the sampling risk” (Messier et al, 2017, p. 267).This intrinsically makes sense: the more of a given entity’s population an auditor samples, the higher his or her confidence in that actual population.
Next, after determining the confidence level, auditors can confirm a sample size “largely by how much tolerable error exceeds expected error.The smaller the difference between these two variables, the more precise the sampling results must be, and therefore the larger the sample size needed” (Messier et al, 2017, p. 267).In straightforward terms, the tolerable error is the error level auditors are willing to accept, while expected error is the assumed error based on the historical defects of whatever metric is being measured.Consequently, the larger the delta of expected over acceptable, the greater the sample size needs to be to be in order to ensure the necessary precision for the audit.
References:
Messier, W. F., Glover, S. M., & Prawitt, D. F XXXXXXXXXXAuditing & Assurance Services: A Systematic Approach (10th ed.). New York: McGraw-Hill/Irwin. ISBN: XXXXXXXXXX