1. Chapter 11 Audit sampling
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

2. Learning objective 1: Definition and features
Audit sampling: the application of an audit procedure to less than 100% of the items within a population to obtain audit evidence about particular characteristics of the population (ASA /ISA ).
Audit sampling is important because it provides information on:
How many items to examine
Which items to select
How sample results are evaluated and extrapolated to the population in order to tell us something about the population (e.g. level of misstatement)
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

3. Sampling risk defined
Sampling risk: the probability that the auditor has reached an incorrect conclusion because audit sampling was used rather than 100% examination (i.e. correctly chosen sample was not representative of the population).
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

4. Non-sampling risk defined
Non-sampling risk: arises from factors, other than sample size, that cause an auditor to reach an incorrect conclusion, such as the possiblility that:
The auditor will fail to recognise misstatements included in examined items
The auditor will therefore apply a procedure that is not effective in achieving a specific objective.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

5. Characteristic of interest
When sampling, the auditor identifies a particular characteristic of the population to focus upon.
For tests of control, the characteristic of interest is the rate of deviation from an internal control policy or procedure.
For substantive tests, the characteristic of interest is monetary misstatement in the balance.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

6. Learning objective 2: Various means of gathering audit evidence
100% examination: this is not a sampling method
Selecting specific items: e.g. high value or high risk — this is not a sampling method. Items selected will not necessarily be representative of the population
Audit sampling
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

7. Statistical sampling defined
Statistical sampling: any approach to sampling that has the following characteristics:
Random sample selection
Use of probability theory to evaluate sample results, including measurement of sampling risk.
Major advantage of statistical sampling over non-statistical sampling methods is defensibility, thorough quantification of sampling risk.
Refer ASA (ISA ).
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

8. Non-statistical sampling
Non-statistical sampling: sampling approaches that do not have all the characteristics of statistical sampling.
Major advantage of non-statistical sampling is greater application of audit experience.
The basic principles and essential procedures identified in ASA 530 (ISA 530) apply equally to both statistical and non-statistical sampling.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

9. Learning objective 3: Planning and designing the sample
Auditor must consider:
Objectives of the audit test (usually related to an audit assertion of interest)
Population from which to sample
Possible use of stratification
Definition of the sampling unit.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

10. Defining the audit objective and population
Once the audit objective is specified, such as reliance on controls or misstatement of account balance, the auditor must consider what conditions would constitute an error.
The auditor must ensure that the population from which the sample is to be selected is complete and appropriate to the audit objective.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

11. Stratification
Stratification: occurs when the auditor divides the population into a series of sub-populations, each of which has an identifying characteristic, such as dollar value.
Can assist with audit efficiency as it allows the auditor to reduce the sample size by reducing variability, without increasing the sampling risk.
Can direct auditor’s attention to areas of audit interest, especially risky or material items.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

12. Defining the sampling unit
Sampling unit is commonly the:
Transactions or balances making up the account balance; or
Individual dollars that make up an account balance or class of transactions, commonly referred to as Probability Proportionate to Size Sampling (PPS) or Dollar Unit Sampling (DUS).
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

13. Learning objective 4: Determining sample size
Sample size is affected by the degree of sampling risk the auditor is willing to accept.
Auditor's major consideration in determining sample size is whether, given expected results from examining sample, sampling risk will be reduced to an acceptably low level.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

14. Factors that influence sample size for tests of controls
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

15. Factors that influence sample size for substantive testing
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

16. Learning objective 5: Selecting the sample
To draw conclusions about population or strata, the sample needs to be typical of characteristics of population or strata.
Sample needs to be selected without bias so that all sampling units in the population or strata have a chance of selection.
Common sampling techniques are:
Random selection — random number generation
Systematic selection
Haphazard selection — select without conscious bias
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

17. Steps in systematic selection
For example, suppose the sample size is 20 and
the number of items in the population is :
Step 1: Calculate the sample interval:
Step 2: Give every item in population chance of selection by choosing a random number (random start) within range of 1 and sampling interval (in this example, 500), e.g. 217.
Step 3: Continue to add sampling interval to random start, and identify items to be sampled, e.g. item nos. 217, 717, , 9717.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

18. Learning objective 6: Performing the audit procedures
To ensure conclusions arising from tests on audit samples are appropriate, auditor must perform testing on each item selected.
If selected item is not appropriate for application of testing procedure, a replacement item can be selected.
If auditor is unable to perform test on a selected item (e.g. loss of documentation), it is considered to be an error.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

19. Evaluating sample results
To evaluate sample results, auditor determines the level of error found in sample and directly projects this error to relevant population. For example: sample 20%, find misstatement of $ Therefore projected error = $ ($10 000/20%).
Projected error is then compared with tolerable error for the audit procedure to determine if characteristic of interest can be accepted or rejected.
Auditor should consider both the nature and cause of any errors identified.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

20. Learning objective 7: Sampling for tests of controls, attribute sampling
Audit sampling is useful for tests of controls, especially involving inspection of source documentation for specific attributes such as evidence of authorisation (attribute sampling).
Involves examination of documents for particular attributes related to controls (e.g. authorisation).
Results of attribute sampling can be used to support or refute an initial assessment of control risk.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

21. Planning and designing sample for tests of controls
Auditor should consider:
Audit objectives (assertions of audit interest)
Tolerable error — maximum error rate that would still support control risk assessment
Allowable risk of over-reliance — allowable risk of assessing control risk too low
Expected error — amount of error the auditor expects to find in the population
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

22. Reliability factors for assessing required confidence level
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

23. Sample size estimation for attribute sampling
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

24. Sample size estimation for attribute samples (alternative method)
An alternative method is to determine sample size by reference to:
Table 11.5 (p. 532), for where allowable risk of over- reliance (ARO) is 10% (90% confidence). This ARO is common in practice.
Table 11.6 (p. 532), for where allowable risk of over- reliance is 5% (95% confidence).
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

25. Evaluation of attribute sample results
Approach in practice is to use sample deviation rate (SDR) as best estimate of population deviation rate.
For example, auditor selects 25 items, finds one error => SDR rate is 4%.
Auditor compares with tolerable deviation rate (TDR). If SDR <= TDR, sample results support auditor’s planned reliance on IC.
If SDR > TDR, sample results do not support auditor’s planned reliance on IC, auditor will revisit audit plan and reduce reliance on IC and increase substantive testing.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

26. Learning objective 8: Sampling for substantive tests
The following matters should be considered:
Relationship of sample to relevant audit objective (assertion of audit interest)
Preliminary judgments about materiality levels
Auditor's allowable risk of incorrect acceptance
Characteristics of the population
Use of other substantive procedures directed at same financial report assertion.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

27. Dollar-unit sampling
Sample unit is individual dollar units, not physical units (transactions or balances). A population with $ that contains 1000 physical units or accounts is viewed as a population with sample units.
Individual dollar selected is attached to that physical unit or account in which it is contained, which will then be tested.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

28. Advantages of dollar-unit sampling (DUS)
Directs auditor’s attention to material items. For example, under traditional sampling, debtor A (owing $10 000) and debtor B (owing $1000) have equal chance of selection. Under DUS, debtor A is ten times more likely to be selected and tested.
Directs auditor’s attention towards overstatement errors.
However, a disadvantage is that it directs auditor’s attention away from understatement errors.
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

29. Determination of sample size for substantive tests
For convenience, this is usually presented as:
E.g. account balance $ Tolerable error $ Expected error is zero and risk of incorrect acceptance is 5%  Reliability factor = 3 (Table 11.4, p. 531)
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

30. Illustration of DUS with systematic selection
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

31. Illustration of DUS with systematic selection (cont.)
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

32. Evaluation of sample results for substantive testing
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

33. Learning objective 9: Other statistical sampling approaches
Mean per unit estimation
Difference estimation
Ratio estimation
Copyright  2007 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 3r by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett