Audit Sampling: How Auditors Select and Test Samples

Auditors rarely test every transaction or balance — it would usually be impractical. Instead, they test a sample and draw conclusions about the whole. Audit sampling is the technique that makes this possible, and understanding it is important for anyone studying or working in audit. This guide explains what audit sampling is, why auditors use it, the main approaches and selection methods, and the risks involved — in clear, plain language. It complements our guide to audit procedures. Auditing standards evolve over time, so always refer to the current standards for authoritative detail.

What is audit sampling?

Audit sampling is the application of audit procedures to less than 100% of the items within a population — such as transactions or balances — in a way that gives the auditor a reasonable basis to draw conclusions about the whole population. Rather than examining every single item, the auditor tests a selected sample and uses the results to form a view about the population as a whole. This is a practical necessity in most audits, given the volume of transactions, but it must be done carefully so that the sample provides meaningful, reliable evidence. Audit sampling is therefore a structured technique, not simply checking a few items at random without thought.

Why auditors use sampling

The main reason auditors use sampling is practicality: testing every item in a large population would usually be far too time-consuming and costly, and isn't necessary to obtain sufficient appropriate evidence. Sampling allows auditors to gather reliable evidence efficiently, focusing their effort where it's needed. The aim is to test enough, in the right way, to support the audit conclusions without testing everything. Of course, because not every item is examined, sampling involves accepting some risk — which is why how the sample is designed, selected and evaluated matters so much. Good sampling balances efficiency with the need for reliable evidence.

Statistical and non-statistical sampling

Audit sampling approaches broadly fall into two types:

• Statistical sampling — uses probability theory to select the sample and evaluate the results, allowing the auditor to measure sampling risk quantitatively.
• Non-statistical sampling — relies more on the auditor's judgement in selecting and evaluating the sample, without the formal statistical measurement.

Both approaches can be valid, and the choice depends on the circumstances and the auditor's judgement. What matters in either case is that the sample is designed and evaluated in a way that provides an appropriate basis for conclusions about the population.

How auditors select samples

There are various methods for selecting the items to test, including:

• Random selection — where every item has an equal chance of being selected, often using random number generators.
• Systematic selection — selecting items at regular intervals through the population.
• Haphazard selection — selecting without a structured technique but also without conscious bias (used with non-statistical sampling).

Auditors may also focus testing on particular items — for example, large or unusual ones — separately from sampling. The aim of the selection method is to produce a sample that's representative of the population, so that conclusions drawn from it are sound. The appropriate method depends on the situation and the auditor's objectives.

Sampling risk and evaluating results

Because auditors test only a sample, there's always a degree of sampling risk — the risk that the conclusion based on the sample differs from the conclusion that testing the whole population would give. Auditors manage this risk through how they design the sample (including its size) and how they evaluate the results. When testing reveals errors in the sample, the auditor considers what this implies for the population as a whole, projecting the findings and assessing whether the population may be materially misstated. Properly designing samples and evaluating results — including following up on errors found — is essential to making sampling a reliable source of audit evidence. As auditing standards develop, the detailed requirements may change, so refer to the current standards.

Frequently asked questions

What is audit sampling?

Applying audit procedures to less than 100% of a population in a way that gives the auditor a reasonable basis to draw conclusions about the whole population.

Why do auditors use sampling?

Mainly for practicality — testing every item in a large population would be too time-consuming and costly, and isn't necessary to obtain sufficient appropriate evidence.

What's the difference between statistical and non-statistical sampling?

Statistical sampling uses probability theory to select and evaluate the sample and measure sampling risk; non-statistical sampling relies more on the auditor's judgement without formal statistical measurement.

What is sampling risk?

The risk that the conclusion based on the sample differs from the conclusion that testing the whole population would give — managed through sample design, size and careful evaluation of results.

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