Practice Advisory 2320-3:
Audit Sampling
…
3. Statistical sampling (e.g., random and systematic) involves the use of techniques from which
mathematically constructed conclusions regarding the population can be drawn. Statistical sampling
allows the auditor to draw conclusions supported by arithmetic confidence levels (e.g., odds of an
erroneous conclusion) regarding a population of data output. It is critical that the sample of
transactions selected is representative of a population. Without ensuring that the sample represents
the population, the ability to draw conclusions based on the review of the sample is limited, if not
erroneous. The internal auditor should validate the completeness of the population to ensure that the
sample is selected from an appropriate data set.
4. Nonstatistical sampling is an approach used by the auditor who wants to use his or her own
experience and knowledge to determine the sample size. Nonstatistical sampling (e.g.,
judgmental) may not be based objectively and, thus, results of a sample may not be mathematically
supportable when extrapolated over the population. That is, the sample may be subject to bias and not
representative of the population. The purpose of the test, efficiency, business characteristics, inherent
risks, and impacts of the outputs are common considerations the auditor will use to guide the sampling
approach. Nonstatistical sampling may be used when results are needed quickly and needed to
confirm a condition rather than being needed to project the mathematical accuracy of the conclusions.
5. In forming an audit opinion or conclusion, auditors frequently do not examine all available
information, as it may be impractical and valid conclusions can be reached using audit sampling.
When using statistical or nonstatistical sampling methods, the auditor should design and select an
audit sample, perform audit procedures, and evaluate sample results to obtain sufficient, reliable,
relevant, and useful audit evidence.
Practice Advisory 2320-3:Audit Sampling…3. Statistical sampling (e.g., random and systematic) involves the use of techniques from whichmathematically constructed conclusions regarding the population can be drawn. Statistical samplingallows the auditor to draw conclusions supported by arithmetic confidence levels (e.g., odds of anerroneous conclusion) regarding a population of data output. It is critical that the sample oftransactions selected is representative of a population. Without ensuring that the sample representsthe population, the ability to draw conclusions based on the review of the sample is limited, if noterroneous. The internal auditor should validate the completeness of the population to ensure that thesample is selected from an appropriate data set.4. Nonstatistical sampling is an approach used by the auditor who wants to use his or her ownexperience and knowledge to determine the sample size. Nonstatistical sampling (e.g.,judgmental) may not be based objectively and, thus, results of a sample may not be mathematicallysupportable when extrapolated over the population. That is, the sample may be subject to bias and notrepresentative of the population. The purpose of the test, efficiency, business characteristics, inherentrisks, and impacts of the outputs are common considerations the auditor will use to guide the samplingapproach. Nonstatistical sampling may be used when results are needed quickly and needed toconfirm a condition rather than being needed to project the mathematical accuracy of the conclusions.5. In forming an audit opinion or conclusion, auditors frequently do not examine all availableinformation, as it may be impractical and valid conclusions can be reached using audit sampling.When using statistical or nonstatistical sampling methods, the auditor should design and select anaudit sample, perform audit procedures, and evaluate sample results to obtain sufficient, reliable,relevant, and useful audit evidence.
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