AUD CH 5 - Audit Sampling Flashcards
Auditing Sampling
examination of LESS THAN 100% of a population & using the results as a basis for drawing a GENERAL (not definitive) conclusion on the entire population (auditor is limited by time — reasonable assurance)
Non-sampling risk
human error
- wrong test
- do not perform tests correctly
Sampling Risk
risk of drawing the wrong conclusion (i.e. risk of projecting a bad sample that does not represent population)
- 2 types of Sampling risk: Efficiency Error & Less Effective
What are the 2 types of Sampling Risk?
Type I – Efficiency Error: population is OK but sample indicates NOT to rely on I/C (incorrectly reject)
Type II – Less Effective: population is BAD but sample indicates to rely on I/C (incorrectly accept)
Explain the effects of Type I (Sampling Risk)
Type I – Efficiency Error (“too conservative”)
Sample indicates NOT to rely on I/C when population is actually OK
- Under-Rely on I/C (too little), Assess RMM too HIGH, DR too LOW, Sub. Testing too HIGH
Therefore, inefficient (incorrectly reject) but still arrive at a valid opinion
Explain the effects of Type II (Sampling Risk)
Type II – Less Effective (“over-aggressive”, wrong answer)
Sample indicates to RELY on I/C when population is actually BAD
- Over-Rely on I/C (too much), Assess RMM too LOW, DR too HIGH, Sub. Testing too LOW
Therefore, less effective, incorrectly accept, & arrive at the wrong opinion
When is sampling used?
- Test of Controls – to determine the operating effectiveness of controls Auditor’s plan to rely on (doesn’t deviate more than tolerable rate)
- Test of Details (sub. procedures) – obtain S.A audit evidence to support management’s assertions
*not during planning phase
If the sample is BAD, and the population is GOOD, what is the sampling risk?
TYPE I – Efficiency Error (UNDER-RELY I/C, RMM TOO HIGH)
If the sample is GOOD & the population is BAD, what is the sampling risk?
TYPE II – Less Effective (OVER-RELY I/C, RMM TOO LOW) —- Wrong Conclusion
When will the auditor want to rely on the control
True Deviation Rate (actual) < Tolerable Deviation Rate
(RMM reduced, DR increased, SUB reduced)
True Deviation Rate (actual) < Tolerable Deviation Rate
Auditor will want to RELY on I/C
(RMM reduced, DR increased, SUB reduced)
When will the auditor NOT want to rely on the control
True Deviation Rate (actual) > Tolerable Deviation Rate
(RMM increased, DR reduced, SUB increased)
True Deviation Rate (actual) > Tolerable Deviation Rate
Auditor will NOT want to rely on the control
(RMM increased, DR reduced, SUB increased)
Which sampling technique is usually applied to test of controls?
Attribute Sampling
What are the 2 risks associated with attribute sampling?
- Risk of Assessing RMM too low (ineffective)
– Sample Deviation Rate < Tolerable Rate…. (Population True Dev > Tolerable) (over-rely on I/C)
- Risk of Assessing RMM too high (Inefficient)
– Sample Deviation Rate > Tolerable Rate.. (under-rely on I/C)… (Population True Dev < Tolerable)
Which sampling technique is usually applied to substantive test of details?
Variable Estimation Sampling
What are the 2 risks risks associated with variable sampling?
- Risk of Incorrect Acceptance (Ineffective):
– Estimated Amount (Sample) is close enough to recorded amount so, the Auditor concludes “materially correct”. Amount is actually materially misstated (therefore, inappropriate conclusion)
- Risk of Incorrect Rejection (Inefficient):
– Sample Amount is different enough from recorded amount . Auditor concludes “materially misstated”, when population is actually “materially correct”, but auditor does unnecessary amount of additional sub. Testing to arrive at the same conclusion
Statistical Sampling
use of quantitative measures of the risk the auditor is taking in the use of sampling (formulas)
- auditor will still have to use judgement to det. Acceptable risk level
Non-statistical Sampling
Judgmental Sampling
- using audit judgement to decided comfort level that conclusions are correct (usually overestimate required sample size)
- effective, but not as efficient using statistical techniques to determine a sufficient sample size
Judgmental Sampling
Non-statistical sampling
Incorrect Acceptance
ineffective Audit with inappropriate conclusion
Incorrect Rejection
inefficient audit with correct conclusion
Assess RMM too LOW
ineffective Audit with inappropriate conclusion
Assess RMM too HIGH
inefficient audit with correct conclusion