In audit sampling, which scenario would typically warrant a smaller sample size?

In audit sampling, which scenario would typically warrant a smaller sample size?

• A. Larger populations with high risk
• B. Higher risk and more heterogeneous populations
• C. Low materiality with complex data
• D. Lower risk and more homogeneous populations

Answer: (D)

Sample size in audit sampling is driven by risk and how much the population varies. When the risk of material misstatement is low and the population is very homogeneous, deviations are less likely and more uniform across the population. That means a small portion of items can reliably represent the whole, so a smaller sample provides sufficient evidence and confidence. In contrast, larger populations with high risk increase the chance of deviations and the need to capture variability; more observations are required to detect problems and reach the same level of assurance. Low materiality with complex data can also complicate the assessment and often pushes for a larger sample to ensure reliable conclusions. Likewise, higher risk and more heterogeneity require bigger samples to accurately estimate deviation rates.

Sample size in audit sampling is driven by risk and how much the population varies. When the risk of material misstatement is low and the population is very homogeneous, deviations are less likely and more uniform across the population. That means a small portion of items can reliably represent the whole, so a smaller sample provides sufficient evidence and confidence.

In contrast, larger populations with high risk increase the chance of deviations and the need to capture variability; more observations are required to detect problems and reach the same level of assurance. Low materiality with complex data can also complicate the assessment and often pushes for a larger sample to ensure reliable conclusions. Likewise, higher risk and more heterogeneity require bigger samples to accurately estimate deviation rates.