Audit Sampling Explained
1. Definition of Audit Sampling
Audit sampling is the application of audit procedures to less than 100% of the items within a population to obtain and evaluate audit evidence about some characteristic of the population.
2. Key Concepts in Audit Sampling
a. Population
The population refers to the entire set of items from which the sample is drawn. For example, if an auditor is examining sales invoices, the population would be all sales invoices issued during a specific period.
Example: A company has 10,000 sales invoices for the year. The population for the audit sample would be all 10,000 invoices.
b. Sample Size
Sample size is the number of items selected from the population for examination. The sample size is determined based on factors such as the desired level of assurance, the expected error rate, and the variability within the population.
Example: An auditor decides to select a sample size of 300 sales invoices from the population of 10,000 to test for accuracy.
c. Sampling Method
Sampling methods include random sampling, systematic sampling, and stratified sampling. Random sampling ensures that each item in the population has an equal chance of being selected. Systematic sampling involves selecting items at regular intervals. Stratified sampling divides the population into subgroups and samples from each subgroup.
Example: The auditor uses random sampling to select 300 invoices from the 10,000-invoice population, ensuring unbiased selection.
d. Sampling Risk
Sampling risk is the risk that the auditor's conclusion based on a sample may be different from the conclusion if the entire population were examined. This includes both the risk of incorrect acceptance (accepting a population as correct when it is not) and the risk of incorrect rejection (rejecting a population as incorrect when it is not).
Example: If the auditor finds no errors in the 300-invoice sample but there are errors in the remaining 9,700 invoices, this is an example of sampling risk.
e. Non-Sampling Risk
Non-sampling risk is the risk that the auditor may reach an incorrect conclusion for reasons other than sampling. This includes errors in audit procedures, misinterpretation of audit evidence, or failure to recognize significant items.
Example: An auditor incorrectly records the results of a test due to a calculation error, leading to an incorrect audit conclusion.
3. Practical Examples
Example 1: Random Sampling
An auditor needs to test the accuracy of payroll payments. The population consists of 5,000 payroll records. The auditor uses a random number generator to select 200 records for testing. This ensures that each payroll record has an equal chance of being selected.
Example 2: Systematic Sampling
An auditor is examining bank reconciliations for the past year. There are 12 reconciliations (one per month). The auditor decides to select every third reconciliation for testing, resulting in four reconciliations being examined.
Example 3: Stratified Sampling
An auditor is testing accounts receivable. The population consists of 1,000 customer accounts, with 100 accounts representing 80% of the total receivables. The auditor decides to sample 50% of the large accounts and 10% of the smaller accounts, ensuring a balanced sample.