Audit Sampling and Data Analysis
Sampling concepts
Audit sampling enables the auditor to obtain evidence about a population. Understand statistical versus non-statistical sampling, sampling risk, and non-sampling risk. Sampling risk is the risk the auditor's conclusion based on a sample differs from a conclusion based on the whole population. Non-sampling risk arises from human error or inappropriate procedures.
Methods and evaluation
Know the sampling methods: random, systematic, monetary unit sampling, and haphazard. Understand how sample size responds to risk, tolerable misstatement, and expected misstatement. For tests of controls, sampling risk includes the risk of assessing control risk too low or too high. For substantive tests, it includes the risk of incorrect acceptance or rejection. Project misstatements to the population and evaluate whether they are material.
Data analysis
Computer-assisted audit techniques allow the auditor to test entire populations, identify anomalies, and perform recalculations. Understand that 100% testing eliminates sampling risk but not non-sampling risk.
Traps in questions
Distractors confuse sampling risk with non-sampling risk, or imply larger samples eliminate non-sampling risk. Another trap suggests haphazard selection is random selection. Watch for confusion between tolerable misstatement and expected misstatement.
Rule of thumb
Larger sample size when risk is higher, tolerable misstatement is lower, or expected misstatement is higher. Sampling risk falls as sample size rises; non-sampling risk does not.
Worked example
If tolerable misstatement falls from 50,000 to 25,000 with other factors constant, the required sample size increases. The auditor should not simply accept the prior year's sample size.