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Chapter 11.docx

2 Pages
Winter 2013

Course Code
ACC 621
Frank Miller

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Chapter 11
Audit Sampling
Remember the number 60 – anything under 60 will probably not be statistically
Two approaches to Sampling
Statistical sampling helps an auditor measure the sufficiency of evidence obtained
and quantitatively evaluate the sampling results
Non-statistical sampling helps the auditor use judgment ay the sufficiency of
Usually a cost vs. benefit is used to decide which measure to take
Sampling Risk – On MC
Sampling risk is the risk that the auditor conclusion based on the sample testing
may be different than the conclusion reached if the audit procedures were applied
to all items in the population
Two Aspect of Sampling Risk
Type I Risk, Alpha Risk (risk of under reliance)
oThe risk the auditor will incorrectly conclude that the specified control is
less effective than it really is
Type II Risk, Beta Risk (Risk of Over Reliance)
oThe risk the auditor will incorrectly conclude that the specified control is
more effective than it really is
Attribute Sampling
Attribute sampling is a statistical approach based on binomial distribution theory
oRichard says “if you test enough you approach the characteristic of the
population you are testing”
Used mostly to test a control as acceptable so you can rely on it
Types of Attribute Sampling
Stratified Attribute Sampling: subdivide the population to test different controls
Stop or Go Sampling: start with low samples and review results
oPeople sometimes stop too early and say everything is great
Discovery Sampling: tries to find where one deviation is and then extrapolate over
the entire population
oTax authorities love this test
Designing Attribute Sampling
Identify specific internal control and the prescribed controls to achieve it
Define what is meant by a standard deviation (what makes the internal controls
not work)

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