Acca aa s21 Notes

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5. Evaluate sample results
When a 
test of controls
is performed, there is a binary outcome for each item selected – either the 
control was applied (effective) or it was not (a ‘deviation’). What proportion of deviations can be 
accepted and still conclude that the control was effective? Say 2%. Suppose that the deviation rate in 
the sample is 4%.
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We would first need to consider the reasons for the deviations. Perhaps some are anomalous (ie 
not representative of the population (eg a purchase invoice was not signed as authorised for 
payment because the manager was in hospital on that date).
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If, excluding the anomalous errors, the deviation rate is still more than 2%, we could increase the 
sample size. If the deviation rate in the bigger sample is not more than 2% – fine. But if more 
than 2%, we cannot rely on the control (as planned) and will have to perform additional 
substantive audit procedures.
For a 
test of details
, which is concerned with the monetary amounts of selected items, any 
misstatements found can be quantified. 
For example, total purchases are $800,000 and the total amount of the sample is $270,000. Suppose 
we are prepared to accept an error in the population of not more than $16,000 (ie 2% of population). 
Errors in the sample total $5,600. Investigation shows that $1,500 is an isolated error (anomaly) and 
$4,100 are due to overpricing.
The error in the population can be projected as: 
Actual error 
×
Population ($)
= $4,100 
×
$(800,000 – 1,500)
= $12,125 (the ‘ratio method’)
Actual error 
×
Sample ($)
= $4,100 
×
$270,000
= $12,125 (the ‘ratio method’)
Total potential misstatement is therefore $13,625 (1,500 + 12,125). As this is less than $16,000, we can 
conclude that purchases are not materially overstated (with whatever degree of confidence 
determined the sample size).
If, however, we had been prepared to accept an error in the population of not more than $8,000 (ie 
1%), clearly some correction is needed. If management agrees to make the corrections for all the 
errors identified, the remaining potential error is $8,025 (13,625 – 5,600). Now we need to exercise 
professional judgment – we might decide we can accept this (just) or extend the test on a larger 
sample.