Sampling and documentation - Sample size, selection, and eva...

Learning Outcomes

After reading this article, you will be able to: define audit sampling and explain its role in gathering sufficient appropriate evidence; distinguish between different sampling methods, including statistical and non-statistical approaches; identify factors influencing sample size and sample selection; describe how to evaluate sample results and take appropriate actions; and state audit documentation requirements for sample procedures and conclusions, all within the context of ACCA Audit and Assurance.

ACCA Audit and Assurance (AA) Syllabus

For ACCA Audit and Assurance (AA), you are required to understand the theory, application, and practical documentation of sampling and selection procedures. Focus your revision on:

• Definition and purpose of audit sampling, and reasons why auditors test less than 100% of a population.
• Differences between statistical and non-statistical sampling, including examples of each.
• Design and selection of samples, such as random, systematic, haphazard, and monetary unit sampling.
• Factors influencing sample size and representativeness.
• Procedures for evaluating sampling results and determining whether additional audit work is necessary.
• Audit documentation requirements for sampling, including recording the rationale, method, and results in the audit file.
• Relationship between sampling risk and detection risk in audit planning and evidence.
• Application and evaluation of sample results in test of controls and substantive procedures.

Test Your Knowledge

Attempt these questions before reading this article. If you find some difficult or cannot remember the answers, remember to look more closely at that area during your revision.

1. Define audit sampling and explain why it is used in an external audit.
2. Identify two key differences between statistical and non-statistical sampling methods.
3. List three factors that influence the size of an audit sample.
4. A test of controls over invoices reveals a 10% deviation rate in the sample. What should the auditor consider next?
5. State the key documentation requirements for audit sampling under ISA 230.

Introduction

Audit sampling enables auditors to obtain sufficient appropriate evidence by testing less than 100% of items within a relevant population. Sampling is essential given practical constraints on time and resources. Proper sample size and selection methods increase audit efficiency and support valid conclusions. Evaluating results ensures that audit objectives are met, while rigorous documentation provides evidence of professional judgement and compliance with ISAs.

Key Term: audit sampling
The application of audit procedures to less than 100% of a population such that all sampling units have a chance of selection, to provide a reasonable basis for conclusions about the whole population.

The Need for Sampling

Testing every transaction or balance is rarely feasible or necessary. Sampling allows auditors to balance audit risk and cost while providing assurance that conclusions drawn are both efficient and reliable. Audit sampling is relevant to both tests of controls and substantive procedures.

Key Term: population
The entire set of data from which a sample is drawn. The population must be appropriate to the audit objective.

Types of Sampling Methods

Audit sampling can be divided into statistical and non-statistical methods. Both require careful design to achieve representative samples.

Key Term: statistical sampling
Any sampling approach that uses random selection and probability theory to evaluate results, allowing quantification of sampling risk.

Key Term: non-statistical sampling
Any sampling method that does not use random selection or probability theory, relying instead on auditor judgement.

Statistical Methods

• Random sampling: Each item has an equal and known chance of selection.
• Systematic sampling: Items are selected using a fixed interval (e.g., every 10th transaction) after a random start.
• Monetary unit sampling: A form of systematic sampling where higher-value items have a greater chance of selection, effective for overstatement risks.

Non-Statistical Methods

• Haphazard sampling: Items are selected at the auditor’s discretion, without conscious bias, but without randomisation.
• Block sampling: Items are selected in contiguous blocks (e.g., all invoices from a particular week), generally discouraged due to risk of bias.

Key Term: sampling risk
The risk that conclusions based on a sample differ from those if the entire population were tested.

Worked Example 1.1

A company has 2,000 sales invoices for the year. The auditor wants to test revenue accuracy. What statistical sampling method could be used, and why?

Answer:
Random sampling could be used to select invoices, ensuring each invoice has a known chance of selection and supporting the auditor’s ability to quantify sampling risk.

Planning and Designing an Audit Sample

Audit sampling must be designed to achieve the audit objective and provide relevant evidence. The following factors influence sample design:

• Population size and characteristics.
• Risk of material misstatement.
• Nature of controls or account balances.
• Expected error or deviation rate.
• Tolerable error (maximum deviation or misstatement auditor is willing to accept).
• The extent of reliance on other audit procedures.

Key Term: tolerable error
The amount of error in the population the auditor is willing to accept without modifying the planned audit approach.

Key Term: expected error
The error rate anticipated by the auditor before sampling, based on prior knowledge.

Determining Sample Size

Sample size is not determined solely by population size. Key considerations include:

• Higher expected error increases sample size.
• Lower tolerable error increases sample size.
• Higher assessed risk of material misstatement demands larger samples.
• Greater reliance on other evidence may reduce sample size.
• Stratification (dividing the population into subgroups) can reduce overall sample size if homogeneity increases.

Worked Example 1.2

You expect a 1% error rate in a 5,000-item population and set tolerable error at 5%. What effect does raising tolerable error to 8% have on the required sample size?

Answer:
Increasing tolerable error reduces required sample size, since the auditor becomes willing to accept more errors before performing further work.

Selecting Items for Testing

Auditors must ensure all items in the population have a chance of inclusion, except in specific selection cases:

• All items: Where populations are small or balances are material by nature (e.g., director transactions), test all items.
• Specific items: Target high value, unusual, or risk-prone items explicitly.
• Sampling: Representative items selected according to designed method.

Key Term: representative sample
A selection whose characteristics reflect those of the entire population, ensuring results are valid.

Worked Example 1.3

The auditor selects all receivable balances over $100,000 for direct testing and samples the remaining smaller balances. What is this approach called?

Answer:
This is stratification—testing all significant items and sampling the rest increases efficiency while ensuring material balances are covered.

Evaluating Sample Results

After performing the audit procedures, the auditor must:

1. Calculate observed deviation or misstatement rate.
2. Project misstatements found in the sample to the entire population.
3. Compare projected error to tolerable error.
4. Consider whether the results indicate isolated or widespread problems.
5. Conclude whether the initial risk assessment remains appropriate or further testing is needed.

Key Term: projected misstatement
The auditor's estimate of misstatement in the entire population, based on sample results.

Key Term: anomaly
An isolated misstatement not representative of the population, usually requiring specific investigation rather than projection.

Exam Warning

Do not project deviations found in tests of controls—focus on deviation rate, not monetary value. For substantive procedures, project misstatements in value terms across the population. Failing to distinguish these could result in incomplete or excessive testing.

If actual error exceeds tolerable error, the auditor must extend testing, reconsider risk assessment, and/or modify the planned nature, timing, or extent of substantive procedures.

Documentation of Sampling Procedures

Proper documentation is essential for audit quality, transparency, and review. Working papers should clearly record:

• The objective and rationale for sampling.
• Definition of population and sampling unit.
• Method of sample selection and sample size.
• Details of items tested and results obtained.
• Evaluation of detected deviations or misstatements.
• Conclusions reached and any further actions taken.

Key Term: audit documentation
The record of audit procedures performed, relevant evidence obtained, and conclusions reached. Documentation must be sufficient for an experienced auditor with no previous connection to the audit to understand the work performed.

Summary Table – Sampling Overview

Key Point Checklist

This article has covered the following key knowledge points:

• Definition and purpose of audit sampling.
• Differences between statistical and non-statistical sampling methods.
• Factors affecting sample size and sampling approach.
• Importance of representative selection and proper documentation.
• Process for evaluating sample results and determining additional procedures.
• Audit working paper content for sampling in accordance with ISAs.

Key Terms and Concepts

• audit sampling
• population
• statistical sampling
• non-statistical sampling
• sampling risk
• tolerable error
• expected error
• representative sample
• projected misstatement
• anomaly
• audit documentation