Audit Sampling


Audit sampling is defined as the application of audit procedures to less than 100% of the items within a population of audit relevance such that all the sampling units have a chance of selection to provide the auditor with a reasonable basis on which to draw the conclusion about the entire population.

The sampling techniques provide each unit in the population with an equal opportunity to be selected. The standard audit sampling makes sure that the auditor will use sampling as an audit technique to draw a conclusion and will not test all the available information as this is time-consuming, practically impossible, and uneconomical.

The audit sampling techniques are widely used in auditing as they allow the auditor to use the minimum number of audit evidence which is not only sufficient but is also authentic and appropriate. Sampling for audit testing also reduces the risk of “over-auditing”.


A Practical Guide to Audit Sampling

Following is an ultimate and practical guide for the auditors to carry out audit sampling in a professional way.

The auditors while conducting sampling for audit testing, should consider the following things.

Selecting A Sample Design

The purpose of sample design in audit sampling is to have a balance between the required precision and the available resources. A sample design must cover the method of selection, sample strength, and the plan to analyze and interpret the results. The sample design may vary from simple to complex depending upon the information required and sample selection method.

Defining The Population

The first step in selecting a good sample design is to make sure that the target population’s stipulations are complete to ensure that all the elements within a population are represented. Sampling frames are usually used to sample the target population. Being an auditor, try to obtain the sample frames in the most automated way to achieve the ease of sampling e.g. database spreadsheet file.

Sample Size

Selecting an appropriate sample size for a particular sample design usually depends upon the following five key factors.

  • The margin of error or precision (the best the design, the less the margin of error and larger the sample size)
  • The amount of variability (the more the variability, the larger the sample size required)
  • The confidence level (the higher the confidence level, the larger the sample size)
  • The population proportion
  • The population size

Weighting A Sample

In some cases, a normal sample is insufficient to include the population characteristics. The auditor is then required to look at the ways in which this can be improved. This is done by weighting the sample. For example, if you are conducting sampling for three regional offices having different workloads, you may want the sample to reflect the workload at each location.

Post weighting the Sample

If the weighting had not taken place at the sample selection stage, it is also possible to weigh the sample in the result phase. This can be done by applying the population proportion to the result of the unweighted sample. This will give an adjusted result for audit sampling.

Selecting Appropriate Sampling Methods

A variety of sampling methods are used by auditors in sampling for audit testing with varying degrees of complexity. Certain methods suit certain circumstances better than others.

  • Multi-stage sampling (suitable for carrying out large surveys of the public)
  • Probability proportional to size (suitable for carrying out offices surveys)
  • Quota sampling (cheap and quick way of obtaining a sample)
  • Random sampling (suitable for simple sample designs and interpretations)
  • Stratified sampling (most reliable representative)
  • Systematic sampling (easier to extract the sample than a simple random method)

Extracting The Sample

Select and extract the sample using either EXCEL OR SPSS. The sample can also be extracted using IDEA.

Interpreting The Results

The results of audit sampling are affected by the sample design chosen and how it reflects the population. Therefore, it is important to choose a sample design relevant to population characteristics. Also, match the calculation of results from the sample to sample design.

Reporting The Results

Finally, report the results of audit sampling considering the following key factors.

  • the sample size
  • the sampling method
  • the estimate resulting from sample
  • the precision and confidence interval for each estimate