We sample to provide reasonable
Conclusion of the whole based on the part
When you apply to anything less than items in population
Attributes sampling: used to estimate the proportion of a population containing a certain characteristic
or attribute
Single deviation is initials and attributes are not having the initials
Error rate of attribute in test of controls
Error rate of transactions for substantive test of transactions
Sampling of balances: used to estimate amount of misstatement present in account balance
Representative sample: needs to be representative of the entire population
Sampling risk: risk we reached wrong conclusion because it is not representative of entire population
Non sampling risk: risk auditor reaches incorrect conclusion because audit tests do not uncover
exceptions in the sample
Statistical:
Requires random sample
You can put a number to sampling risk if you have used a statistical approach
Judgemental – may use non random sampling – just clicking on a random item
Plan sample
Select sample
Our goal is to say are controls working well enough to rely on, and does it support original control risk
assessment
Transaction goal: are they being recorded correctly enough?
We can say everything is good or reevaluate misstatements
We sample to provide reasonable
Tolerable exception rate- highest deviation rate we are willing to accept to rely on control or say
statements are good enough
Acceptable risk of overreliance – what risk are we willing to take that control is relying better than you
would think
Estimated population exception rate – what we think the rate of misstatements or control deviation is
Need this to plan sample size
Sample exception rate – no. of exceptions/sample size
Computed upper exception rate (CUER): highest estimated exception rate in the population for a given
ARO and sample result
Aria and aro risk that you said everything is good but that is not the truth
Tolerable misstatement as % - self explanatory
Ratio of estimated population misstatement to tolerable misstatement
Confidence factor – represents how strongly we need to feel we came to write conclusion about sample
and population
Higher numbers means we need to look at a lot more
$50000
10000 misstatement expected
Tolerable 20000
.5 ratio between the two
15000/20000 = .5