1. Chapter 11 Audit sampling
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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.
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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

3. Non-sampling and sampling risk defined
Sampling risk: the probability that the auditor has reached an incorrect conclusion because audit sampling was used rather than 100% examination (ASA/ISA ).
Non-sampling risk: arises from factors, other than sample size, that cause an auditor to reach an incorrect conclusion, such as the possibility that:
The auditor will fail to recognise misstatements included in examined items
The auditor applies a procedure that is not effective in achieving a specific objective.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

4. 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

5. 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

6. Statistical and non-sampling sampling
Statistical sampling: an approach to sampling that has the following characteristics:
Random sample selection
Use of probability theory to evaluate sample results
Major advantage is defensibility, thorough quantification of sampling risk
Refer ASA/ISA (g)
Non-statistical sampling: sampling approaches that do not have all the characteristics of statistical sampling.
Major advantage is greater application of audit experience
The basic principles and essential procedures identified in ASA/ISA 530 apply equally to both statistical and non-statistical sampling.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

7. Current practice in Australia and business risk assessment
In Australia, there are some disparities with regard to the practice of sampling within the large audit firms.
Firms will usually use an unbiased approach but the size of the sample they select will usually be determined with the help of decision aids within the firm.
Sample sizes that are commonly used in practice are around 20 items where a moderate level of testing is required, or 30 items where more extensive levels of testing are undertaken.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

8. Basic requirements of all audit samples
Whenever an auditor uses audit sampling (statistical
or non-statistical) the following requirements apply:
Planning and design: The auditor considers the relationship of the sample to the relevant specific audit objective or control objective and considers certain other factors that should influence sample size.
Selection: Sample items are selected in such a way that the sample can be expected to be representative of the population.
Performing the procedure and evaluating results: The auditor performs the required audit procedures on the items selected, projects the results of the audit procedures undertaken on the sample to the population and considers sampling risk.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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 (ASA 530/ISA 530 Appendix 1, paragraphs 1–4).
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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

12. Defining the sampling unit
The 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 Monetary-Unit Sampling (MUS) or Dollar Unit Sampling (DUS).
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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 (ASA/ISA ).
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

14. Factors that influence sample size for tests of controls
Appendix 2 to ASA/ISA 530 outlines the factors that influence sample size for tests of controls as follows:
The extent to which the auditor’s risk assessment takes into account relevant controls (control risk assessment)
The tolerable rate of deviation
The expected rate of deviation
The auditor’s desired level of assurance
The number of sampling units in the population.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

15. Factors that influence sample size for substantive testing
Appendix 3 to ASA/ISA 530 outlines the factors that influence sample size for substantive testing as follows:
The auditor’s assessment of risk of material misstatement
The use of other substantive procedures directed at the same assertion
The auditor’s desired level of assurance that actual misstatement is not greater than tolerable misstatement
The tolerable misstatement
The amount of misstatement the auditor expects to find in the population (expected misstatement)
Stratification
The number of sampling units in the population.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

16. Learning objective 5: Selecting the sample
To draw conclusions about population or stratum, the sample needs to be typical of characteristics of population or stratum.
Sample needs to be selected without bias so that all sampling units in the population or stratum have a chance of selection.
Common sampling techniques are:
Random selection — random number generation
Systematic selection
Haphazard selection — select without conscious bias.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

18. Biases from haphazard sampling
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

19. Unacceptable sample selection methods
Block selection: the auditor selects all items of a specified type processed on a particular day, week or month.
Judgmental selection (based on sample item characteristics): the auditor selects large or unusual items from the population or uses some other judgmental criterion for selection.
This method has a conscious bias and cannot be considered representative.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

20. 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 (ASA/ISA 530.9–10).
If auditor is unable to perform test on a selected item (e.g. loss of documentation), it is considered to be an error.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

21. Evaluating sample results
To evaluate sample results, auditor determines the level of misstatement found in sample and directly projects this misstatement to relevant population. For example: sample 20%, find misstatement of $ Therefore projected misstatement = $ ($10 000/20%).
Projected misstatement is then compared with tolerable misstatement 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 misstatement or deviations identified.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

22. 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

23. Planning and designing sample for tests of controls
Auditor should consider:
Audit objectives (assertions of audit interest)
Control risk assessment and tolerable deviation rate
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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

24. Audit objectives
A sampling technique that is suitable for tests of controls is attribute sampling.
The following steps are necessary in considering the relationship between the sample and the objective of the test:
Identify relevant control objectives, policies and procedures that are relevant to restricting substantive tests of the related account balances.
Identify population and sample unit.
Define the characteristic of interest – so that an attribute either exists or does not exist which means that a control activity has either been complied with or not complied with.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

25. Control risk assessment and tolerable deviation rate
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

26. Reliability factors for assessing required confidence level
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

27. Sample size estimation for attribute sampling
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

28. Sample size estimation for attribute samples (alternative method)
An alternative method is to determine sample size by
reference to:
Table 11.3 (p. 566), for where allowable risk of over- reliance (ARO) is 10% (90% confidence). This ARO is common in practice.
Table 11.4 (p. 567), for where allowable risk of over- reliance is 5% (95% confidence).
For example, where desired level of assurance is 90%, (Table 11.3), tolerable deviation rate is 10%, and expected deviation rate is 0, required sample size is 22.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

29. Selection of sample items for tests of controls
Having determined the appropriate sample size, it is then a matter of determining which sample items to select.
The representative selection methods of random selection and systematic selection generally apply to both tests of controls and substantive tests.
However, stratification is not usually applicable to tests of controls.
Systematic selection is often useful for tests of controls because it helps to achieve the auditor’s internal control objective of testing continuity of controls by ensuring sampling is continuous throughout the year.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

30. 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 need to consider reliance on IC and may consequentially increase substantive testing.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

31. Learning objective 8: Planning 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

32. 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, and the unit or account will then be tested.
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

33. 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  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

34. 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 11.5, p. 572)
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

35. Illustration of DUS with systematic selection
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

36. Illustration of DUS with systematic selection (cont.)
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

37. Evaluation of sample results for substantive testing
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett

38. Learning objective 9: Other statistical sampling approaches
Mean per unit estimation
Difference estimation
Ratio estimation
Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett
Slides prepared by Roger Simnett