Which sampling method is MOST useful when testing for compliance?

Attribute sampling is particularly effective for testing compliance because it evaluates whether specific attributes or characteristics are present or absent in a population. This method focuses on assessing compliance with established criteria, typically resulting in a simple "pass" or "fail" outcome for each sampled item.

In compliance testing, the objective is often to determine whether a set of requirements, regulations, or controls are being adhered to. Since attribute sampling enables auditors to draw conclusions about the proportion of items in compliance versus those that are not, it is the preferred method for such assessments. The results can provide a clear indication of compliance levels and help in making informed decisions based on the findings.

Other methods, like variable sampling, are more suited for detailed quantitative analyses rather than binary compliance checks. Stratified mean-per-unit sampling provides a mean estimate across different strata, which may be useful for general assessments but does not directly address compliance in the same straightforward manner as attribute sampling. Difference estimation sampling focuses on estimating the difference between two populations or conditions, which again diverges from the primary goal of compliance testing.