7. Audit Sampling Flashcards
Meaning of Audit Sampling.
According to SA 530 “Audit sampling”, ‘audit sampling’ refers to the application of audit procedures to less than 100% of items within a population relevant under the audit, such that all sampling units (i.e all the items in the population) have an equal chance of selection.
This is to ensure that the items selected represent the entire population which enables the auditor to draw conclusions and express his opinion about the entire population.
What is population and characteristics of population.
Population refers to the entire set of data from which a sample is selected and about which the auditor wishes to draw conclusions.
The auditor should select sample items in such a way that the sample can be expected to be representative of the population. This requires that all items in the population have an opportunity of being selected.
Characteristics of Population:-
1. Appropriateness:
The auditor will need to determine that the population from which the sample is drawn is appropriate for the specific audit objective.
- Completeness:
The population also needs to be complete, which means that if the auditor intends to use the sample to draw conclusions about whether a control activity is operated effectively during the financial reporting period, the population needs to include all relevant items throughout the entire period. - Reliable:
When performing the audit sampling, the auditor performs audit procedures to ensure that the information upon which the audit sampling is performed is sufficiently complete and accurate.
Approaches to Sampling (Types of Sampling).
Audit sampling can be applied using either non-statistical or statistical sampling approaches.
- Statistical sampling:
Statistical sampling is an approach to sampling that has the
i) random selection of the sample units; and
ii) the use of probability theory to evaluate sample results, including measurement of sampling risk characteristics.
Audit testing done through this approach is more scientific than testing based entirely on the auditor’s own judgment because it involves use of mathematical laws of probability in determining the appropriate sample size in varying circumstances.
There Is no personal bias of the auditor in case of statistical sampling.
- Non-statistical sampling:
A sampling approach that does not have the above features is considered as non-statistical sampling.
Under this approach, the sample size and its composition are determined on the basis of the personal experience and knowledge of the auditor.
This approach has been in common application for many years because of its simplicity in operation.
Criticism about Non-statistical sampling approach.
The non-statistical sampling is criticized on the grounds that-
i) It is neither objective nor scientific.
ii) The expected degree of objectivity cannot be assured in non statistical sampling because the risk of personal bias in selection of sample items cannot be eliminated.
iii) The closeness of the qualities projected by the sample results with that of the whole population cannot be measured because the sample has not been selected in accordance with the mathematically based statistical techniques.
What factors are to be considered for deciding the extent of checking based on sample?
The factors that should be considered for deciding upon the extent of checking on a sampling plan are as follows:
i) Size of the organisation under audit.
ii) State of the internal control.
iii) Adequacy and reliability of books and records.
iv) Tolerable error range.
v) Degree of the desired confidence.
Advantages of statistical sampling.
The advantages of statistical sampling may be summarized as follows
1) The amount of testing (sample size) does not increase in proportion to the increase in the size of the area (universe) tested.
2) The sample selection is more objective and thereby more defensible.
3) The method provides a means of estimating the minimum sample size associated with a specified risk and precision.
4) It provides a means for deriving a “calculated risk” and corresponding precision (sampling error) i.e. the probable difference in result due to the use of a sample in lieu of examining all the records in the group (universe), using the same audit procedures.
5) It may provide a better description of a large mass of data than a complete examination of all the data, since non-sampling errors such as processing and clerical mistakes are not as large.
6) It is a widely accepted way of sampling as it is more scientific, without personal bias and the result of the sample can be evaluated and projected in more reliable way.
What is stratification selection?
In considering the characteristics of the population from which the sample will be drawn, the auditor may determine that stratification or value-weighted selection is appropriate.
Stratification:
Audit efficiency may be improved if the auditor stratifies a population by dividing it into discrete sub-populations which have an identifying characteristic.
The objective of stratification is to reduce the variability of items within each stratum and therefore allow sample size to be reduced without increasing sampling risk.
When performing tests of details, the population is often stratified by monetary value. This allows greater audit effort to be directed to the larger value items, as these items may contain the greatest potential misstatement in terms of overstatement.
Similarly, a population may be stratified according to a particular characteristic that indicates a higher risk of misstatement.
How auditor determines the sample size?
The auditor shall determine a sample size sufficient to reduce sampling risk to an acceptably low level.
The level of sampling risk that the auditor is willing to accept affects the sample size required.
The lower the rsk the auditor is willing to accept, the greater the sample size will need to be.
Sample selection methods.
Sample should be selected in such a manner that it is representative of the population from which the sample is being selected. It will necessitate that each item in the population has an equal chance of being included in the sample.
Some of the important methods of selecting the sample are discussed below -
1) Random Sampling:
Random selection ensures that all items in the population or within each stratum have a known chance of selection. Random sampling includes two very popular methods which are discussed below
i) Simple Random Sampling:
Under this method each unit of the whole population has an equal chance of being selected.
Each item in a population is selected by use of random number table either with a help of computer or picking up a number in a random way (may be randomly from a drum).
This method is considered appropriate provided the population to be sampled consists of reasonably similar units and fall within a reasonable range i.e it is suitable for a homogeneous population having a similar range.
ii) Stratified Sampling:
This method involves dividing the whole population to be tested in a few separate groups called strata and taking a sample from each of them.
Each stratum is treated as if it was a separate population.
The number of groups into which the whole population has to be divided is determined on the basis of auditor judgment.
2) Interval Sampling or Systematic Sampling:
Systematic selection is a selection method in which the number of sampling units in the population is divided by the sample size to give a sampling interval, for example 50, and having determined a starting point within the first 50, each 50th sampling unit thereafter is selected.
When using systematic selection, the auditor would need to determine that sampling units within the population are not structured in such a way that the sampling interval corresponds with a particular pattern in the population.
3) Monetary Unit Sampling:
It is a type of value-weighted selection in which sample size, selection and evaluation results in a conclusion in monetary amounts.
4) Haphazard sampling:
Haphazard selection, in which the auditor selects the sample without folowing a structured technique.
Although no structured technique is used, the auditor would nonetheless avoid any conscious bias or predictability (for example, avoiding difficult to locate items, or always choosing or avoiding the first or last entries on a page) and thus attempt to ensure that all items in the population have a chance of selection.
Haphazard selection is not appropriate when using statistical sampling.
5) Block Sampling:
This method involves selection of a block(s) of contiguous items from within the population.
Block selection cannot ordinarily be used in audit sampling because most populations are structured such that items in a sequence can be expected to have similar characteristics to each other, but different characteristics from items elsewhere in the population.
Nature and cause of deviations and misstatements.
i) In analyzing the deviations and misstatements identified, the auditor may observe that many have a common feature, for example, type of transaction, location, product line or period of time.
ii) In such circumstances, the auditor may decide to identify all items in the population that possess the common feature, and extend audit procedures to those items.
iii) In addition, such deviations or misstatements may be intentional, and may indicate the possibility of fraud.
iv) In the extremely rare circumstances when the auditor considers a misstatement or deviation discovered in a sample to be an anomaly, the auditor shall obtain a high degree of certainty that such misstatement or deviation is not representative of the population.
v) The auditor shall obtain this degree of certainty by performing additional audit procedures to obtain sufficient appropriate audit evidence that the misstatement or deviation does not affect the remainder of the population.
Projecting misstatements
i) The auditor is required to project misstatements for the population to obtain a broad view of the scale of misstatement but this projection may not be sufficient to determine an amount to be recorded.
ii) When a misstatement has been established as an anomaly, it may be excluded when projecting misstatements to the population. However, the effect of any such misstatement, if uncorrected, still needs to be considered in addition to the projection of the non-anomalous misstatements.
iii) For tests of details, the auditor shall project misstatements found in the sample to the population whereas for tests of controls, no explicit projection of deviations is necessary since the sample deviation rate is also the projected deviation rate for the population as a whole.
