What Is Sampling?
Sampling is a process in statistical analysis where researchers take a predetermined number of observations from a larger population. The method of sampling depends on the type of analysis being performed, but it may include simple random sampling or systematic sampling.
- Certified Public Accountants use sampling during audits to determine the accuracy and completeness of account balances.
- Types of sampling include random sampling, block sampling, judgement sampling, and systematic sampling.
- Companies use sampling as a marketing tool to identify the needs and wants of their target market.
How Sampling is Used
A Certified Public Accountant (CPA) performing a financial audit uses sampling to determine the accuracy and completeness of account balances in the financial statements. Sampling performed by an auditor is referred to as "audit sampling."
It is necessary to perform audit sampling when the population, in this case account transaction information, is large. Additionally, managers within a company may use customer sampling to assess the demand for new products or the success of marketing efforts.
The chosen sample should be a fair representation of the entire population. When taking a sample from a larger population, it is important to consider how the sample is chosen. To get a representative sample, it must be drawn randomly and encompass the whole population. For example, a lottery system could be used to determine the average age of students in a university by sampling 10% of the student body.
Types of Audit Sampling
With random sampling, every item within a population has an equal probability of being chosen. It is the furthest removed from any potential bias because there is no human judgement involved in selecting the sample.
For example, a random sample may include choosing the names of 25 employees out of a hat in a company of 250 employees. The population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen.
Auditor judgement may be used to select the sample from the full population. An auditor may only be concerned about transactions of a material nature. For example, assume the auditor sets the threshold for materiality for accounts payable transactions at $10,000. If the client provides a complete list of 15 transactions over $10,000, the auditor may just choose to review all transactions due to the small population size.
Alternatively, an auditor may identify all general ledger accounts with a variance greater than 10% from the prior period. In this case, the auditor is limiting the population from which the sample selection is being derived. Unfortunately, human judgement used in sampling always comes with the potential for bias, whether explicit or implicit.
Block sampling takes a consecutive series of items within the population to use as the sample. For example, a list of all sales transactions in an accounting period could be sorted in various ways, including by date or by dollar amount.
An auditor may request that the company's accountant provide the list in one format or the other in order to select a sample from a specific segment of the list. This method requires very little modification on the auditor's part, but it is likely that a block of transactions will not be representative of the full population.
Systematic sampling begins at a random starting point within the population and uses a fixed, periodic interval to select items for a sample. The sampling interval is calculated as the population size divided by the sample size. Despite the sample population being selected in advance, systematic sampling is still considered random if the periodic interval is determined beforehand and the starting point is random.
Assume that an auditor is reviewing the internal controls related to a company's cash account and wants to test the company policy that stipulates that checks exceeding $10,000 must be signed by two people. The population consists of every company check exceeding $10,000 during the fiscal year, which, in this example, was 300. The auditor uses probability statistics and determines that the sample size should be 20% of the population or 60 checks. The sampling interval is 5 (300 checks / 60 sample checks).
Therefore, the auditor selects every fifth check for testing. Assuming no errors are found in the sampling test work, the statistical analysis gives the auditor a 95% confidence rate that the check procedure was performed correctly. The auditor tests the sample of 60 checks and finds no errors, so he concludes that the internal control over cash is working properly.
Example of Marketing Sampling
Businesses aim to sell their products and/or services to target markets. Before presenting products to the market, companies generally identify the needs and wants of their target audience. To do so, they may employ sampling of the target market population to gain a better understanding of those needs to later create a product and/or service that meets those needs. In this case, gathering the opinions of the sample helps to identify the needs of the whole.