Audit sampling is an essential part of the auditing process, enabling auditors to draw conclusions about a larger population by examining a smaller subset of items. There are several types of audit sampling methods, each with its specific approach and application. Understanding these different types allows auditors to select the most appropriate method based on the nature of the audit, the objectives, and the characteristics of the population being examined.
1. Statistical Sampling
Statistical sampling involves the use of mathematical and statistical principles to determine the sample size, select the sample, and evaluate the results. This method provides a quantifiable measure of the sampling risk—the risk that the auditor’s conclusion based on the sample might be different from the conclusion if the entire population were tested. Statistical sampling is highly regarded for its objectivity and the precision it offers.
- Random Sampling: This is the most common form of statistical sampling. In random sampling, each item in the population has an equal chance of being selected. This randomness helps ensure that the sample is representative of the entire population. The random selection can be achieved through various means, such as using random number tables or computer-generated random numbers.
- Systematic Sampling: In systematic sampling, the auditor selects items using a fixed interval. For example, if the population is 1,000 items and the desired sample size is 50, the auditor might select every 20th item after choosing a random starting point. While systematic sampling can be more efficient than random sampling, it requires that the population is not ordered in a way that could introduce bias.
- Stratified Sampling: Stratified sampling involves dividing the population into subgroups (strata) based on specific characteristics, such as value ranges or types of transactions. A sample is then drawn from each stratum. This method is particularly useful when the population is heterogeneous, as it ensures that each subgroup is appropriately represented in the sample.
- Probability-Proportional-to-Size (PPS) Sampling: PPS sampling, also known as dollar-unit sampling, selects sample items based on their monetary value. Larger items have a higher probability of being selected, making this method particularly effective when testing for overstatements in financial statements. This technique is frequently used in auditing accounts receivable, inventory, and other balance sheet items.
2. Non-Statistical (Judgmental) Sampling
Non-statistical sampling relies on the auditor’s professional judgment rather than mathematical methods to determine the sample size and select the sample. While it does not provide a quantifiable measure of sampling risk, it is still widely used due to its flexibility and ease of application.
- Haphazard Sampling: In haphazard sampling, the auditor selects items arbitrarily without using a structured or random method. While the selection is intended to be without bias, the lack of structure means it is more prone to unconscious biases. Haphazard sampling is typically used when the auditor needs a quick assessment or when the population is homogenous.
- Block Sampling: Block sampling involves selecting a consecutive series of items from the population. For example, an auditor might choose to examine all transactions in a particular week or month. While this method is easy to apply, it may not always provide a representative sample, especially if there are seasonal trends or other patterns within the population.
- Judgmental Sampling: Judgmental sampling is entirely based on the auditor's expertise and knowledge of the client's business. The auditor uses their judgment to select items they believe are most likely to contain errors or are of particular importance. This method is often used in conjunction with other sampling techniques to focus on high-risk areas or when specific characteristics of the population suggest that errors may be concentrated in certain items.
3. Dual-Purpose Sampling
Dual-purpose sampling serves two purposes simultaneously, typically involving both substantive testing and tests of controls. This method is used when the auditor wants to maximize the efficiency of the audit by using a single sample to achieve multiple objectives. For example, the auditor might use dual-purpose sampling to test the accuracy of recorded transactions (substantive test) while also evaluating the effectiveness of internal controls over those transactions (test of controls).
4. Attribute Sampling
Attribute sampling is used primarily in tests of controls, where the objective is to estimate the rate of occurrence of a specific characteristic or error within the population. For example, an auditor might use attribute sampling to test whether transactions were properly authorized by examining a sample of purchase orders for appropriate approvals.
- Fixed Sampling: A fixed sample size is selected, and the occurrence rate of the characteristic or error is measured. The results are then compared against the auditor’s tolerable rate of error to determine if the control is operating effectively.
- Discovery Sampling: Discovery sampling is a type of attribute sampling used when the auditor expects the occurrence of errors to be rare. The objective is to discover at least one occurrence of the error in the sample. If an error is found, the auditor may conclude that the control is not operating effectively and may need to expand the sample or adjust their audit approach.
5. Variable Sampling
Variable sampling is used primarily in substantive testing to estimate the amount of error in a population. Unlike attribute sampling, which focuses on the presence or absence of a characteristic, variable sampling measures the actual value of the characteristic being tested. This method is particularly useful for testing account balances and other financial statement items.
- Mean-per-Unit (MPU) Sampling: MPU sampling involves calculating the mean value of the items in the sample and projecting it to the entire population. This method is straightforward but assumes that the population is homogenous.
- Difference Estimation: Difference estimation compares the audited values of items in the sample with their recorded values to estimate the total misstatement in the population. This method is effective when the auditor expects that the recorded values might be systematically misstated.
- Ratio Estimation: Ratio estimation involves calculating the ratio of audited values to recorded values in the sample and applying this ratio to the entire population to estimate the total misstatement. This method is useful when the misstatements are expected to be proportional to the size of the items.
Audit sampling is a versatile and powerful tool that allows auditors to perform their work efficiently and effectively. By understanding and selecting the appropriate type of sampling, auditors can gather reliable evidence, draw accurate conclusions, and fulfill their responsibilities with confidence. Whether using statistical or non-statistical methods, the key is to ensure that the sample is representative and that the results are interpreted with an awareness of the inherent risks and limitations of the sampling process.
