What is statistical sampling in auditing?

Statistical sampling in auditing refers to the use of mathematical techniques to select a sample from a population in a way that allows auditors to make inferences about the entire population based on the sample results. This method typically involves using probabilities to determine sample sizes and selection methods, ensuring that the sample is representative of the larger population.

By utilizing both numerical and proportional sampling, auditors can ensure that different aspects of the data are adequately represented in the sample, allowing for more reliable results and conclusions. This approach minimizes bias and enhances the validity of the audit findings, facilitating better risk assessment and decision-making.

Other options do not align with the principles of statistical sampling. For instance, sampling based purely on auditor intuition lacks the systematic and probabilistic rigor required for effective statistical sampling. Choosing samples from only one segment of the data population may introduce bias, as it does not provide a comprehensive view of the entire population. Lastly, while prior audit experiences can inform the sampling process, they are not a requirement for statistical sampling, which depends more on established methodologies and statistical principles.