Introduction
Audit sampling is more than just theory — it plays a pivotal role in how auditors gather and evaluate evidence. By examining representative subsets of large populations, auditors can reach conclusions about financial data with a high degree of confidence. In this article, we present five real-world audit sampling examples that illustrate how professionals apply sampling in diverse audit scenarios.
Whether you’re an aspiring auditor or a seasoned practitioner, understanding how sampling techniques translate into fieldwork will enhance your audit planning and execution.
Example 1: Random Sampling to Test Sales Invoices
Scenario: An auditor is auditing the revenue of a retail company with over 20,000 sales transactions in the year.
Steps:
- Define population: All sales invoices for the year.
- Determine sample size based on materiality, expected error rate, and audit risk.
- Use a random number generator to select 120 invoices.
- Examine invoices for proper authorization, pricing accuracy, and supporting shipping documents.
- Evaluate results—if no major deviations are found, conclude revenue transactions are fairly stated.
Technique used: Statistical—random sampling
Why this works: Ensures an unbiased sample from a large homogeneous population.
Example 2: Stratified Sampling in Expense Auditing
Scenario: A manufacturing client has operating expenses ranging from $10 to $1,000,000.
Steps:
- Stratify the population into three groups:
- Low-value (< $5,000)
- Medium-value ($5,000–$100,000)
- High-value (> $100,000)
- Sample more heavily from the high-value stratum.
- Perform tests to ensure expenses are valid, authorized, and correctly recorded.
- Analyze misstatements to project the potential impact by strata.
Technique used: Non-statistical—stratified sampling
Why this works: Maximizes audit efficiency by focusing on high-risk transactions.
Example 3: Monetary Unit Sampling for Receivables Testing
Scenario: The client has $6 million in accounts receivable with 4,000 accounts.
Steps:
- Use MUS to give larger dollar balances a higher chance of selection.
- Select 60 sample items based on the calculated interval.
- Send confirmation letters to verify existence and accuracy.
- Follow up on discrepancies and evaluate exceptions.
Technique used: Statistical—Monetary Unit Sampling (MUS)
Why this works: Effective for detecting overstatements, especially in revenue-related balances.
Example 4: Systematic Sampling for Payroll Testing
Scenario: An auditor reviews weekly payrolls for a logistics firm with 2,600 employees.
Steps:
- Define interval—select every 100th employee from the payroll register.
- Randomize the starting point.
- Examine documentation such as timecards, approvals, rate consistency.
- Test calculations for accuracy and authorization.
Technique used: Statistical—systematic sampling
Why this works: Maintains consistency while reducing the risk of missing systemic errors.
Example 5: Haphazard Sampling for Cash Disbursement Review
Scenario: An auditor performs walkthrough procedures on cash payments.
Steps:
- Select 20 disbursements haphazardly from the cash book.
- Test for proper approval, valid supporting documents, and recording accuracy.
- Document rationale for selection method and findings.
Technique used: Non-statistical—haphazard sampling
Why this works: Useful in small populations where formal statistical methods are impractical.
Summary Table: Techniques and Use Cases
| Sampling Technique | Audit Area | Type | Best Used For |
|---|---|---|---|
| Random Sampling | Sales transactions | Statistical | Large homogeneous data sets |
| Stratified Sampling | Expenses | Non-Statistical | Mixed-value populations |
| Monetary Unit Sampling | Accounts receivable | Statistical | High-dollar overstatement detection |
| Systematic Sampling | Payroll | Statistical | Evenly distributed data |
| Haphazard Sampling | Cash disbursements | Non-Statistical | Small or informal testing populations |
Conclusion
These audit sampling examples demonstrate the importance of selecting the right technique based on audit objectives, risk levels, and population characteristics. Whether using statistical methods like MUS or relying on judgmental approaches like stratification, auditors must apply sampling with clarity and care to ensure credible audit outcomes.
Understanding real-world applications of sampling techniques strengthens audit effectiveness and helps auditors comply with international standards.
References
- ISA 530: Audit Sampling – International Auditing and Assurance Standards Board (IAASB)
- PCAOB AS 2315: Audit Sampling
- Messier, W., Glover, S., & Prawitt, D. (2022). Auditing & Assurance Services: A Systematic Approach. McGraw-Hill.