Study Unit 14 - Evidence - Sampling Flashcards
Define the confidence level in statistical sampling.
The confidence level (reliability level) is the percentage of times the sample should adequately reflect the population. It is the complement of the applicable sampling risk factor. For example, if the allowed risk is 5%, the auditor’s desired confidence level is 95% (100%-5%)
What are the statistical sampling methods applies to (1) test of controls and (2) tests of detail and what do the assess?
Audit Test Sampling Method Assessment
Test of Attribute Expected deviation
Controls Sampling rate (percentage)
Test of Variables Expected misstatement
details sampling (dollar amount)
What is the sampling risk?
Sampling risk is the risk that the auditor’s conclusion based on sample may differ from the conclusion when the same procedure is applied to the entire population.
What are the two types of erroneous conclusions regarding the sampling of (1) tests of controls and (2) test of details?
Test of Controls Test of Details
(Attribute Sampling) (Variables Sampling)
Audit Efficiency Sampled controls Sample indicates a
Error less effective than material misstatement
(Unnecessary they actually are exists when in fact it
Audit effort) (Underreliance) does not (Incorrect
acceptance)
Audit Effective-
Ness Sampled controls Sample indicates a
Error (Potential are more effective material misstatement
Audit failure) than they actually does not exist when in
are (Overreliance) fact it does (Incorrect
acceptance)
When the expected deviation rate is high for tests of controls or the expected misstatement is high for tests of details, how are audit procedures affected?
High expected deviation rate Reduces reliance on tests of control
(Tests of controls) (nonreliance in extreme cases)
High expected misstatement Increases sample size
(Tests of details) (100% audit in extreme cases)
What is the desired level of assurance regarding the sampling of (1) tests of controls and (2) test of details?
Audit Test Level of Assurance (confidence level)
Test of controls Complement of the risk of overreliance
(Actual deviation rate > Tolerable rate)
Test of details Complement of the risk of incorrect acceptance
(Actual misstatement > Tolerable misstatement)
EXAMPLE: If the allowed rick of overreliance/incorrect acceptance is 5%, the level of assurance is 95%.
What is the random sampling method?
In random sampling, each item in the population has an equal and nonzero probability of selection.
What is the stratified sampling method?
In stratified sampling, the population is divided into sub populations (strata) and then samples are randomly selected from within the strata. The primary objective of stratification is to minimize variability.
Give examples of common variables sampling methods.
- Mean-per-unit method
- Difference estimation method
- Ratio estimation method
- Monetary-unit sampling (MUS) method
Monetary-unit sampling (MUS) is most useful for testing for (1) ______ (e.g., assets) if (2) ______ misstatements are expected.
- Overstatement
- Few
Describe attribute sampling.
Attribute sampling tests binary (yes/no or error/nonerror) questions. It tests the effectiveness of controls because it can estimate a rate of occurrence of control deviations (e.g., unsigned purchase orders) in a population.
What are the three factors that determine the sample size in audit attribute sampling?
- Allowable risk of overreliance
- Tolerable deviation rate
- Expected population deviation rate
In attribute sampling, what are the relationships (direct or inverse) between the sample size and (1) allowable risk of overreliance, (2) tolerable deviation rate, and (3) expected population deviation rate?
Factor Relationship with sample size
Allowable risk of overreliance Inverse
Tolerable deviation rate Inverse
Expected population deviation rate Direct
In attribute sampling, how is the sample deviation rate calculated?
Sample deviation rate = Number of deviations observed / Sample Size
In attribute sampling, what is the allowance for sampling risk?
The allowance for sampling risk is the difference between the achieved upper deviation limit (determined from a standard table) and the sample deviation rate.
