AbstractUsing experimental data from their signal-detection study, the authors examine traditional measures of inspector performance along with measures based on Bayes'rule. Results indicate that the inspector's decision process is affected by the a priori probability of nonconforming product in the inspection lot and that inspector decision error may result in a tighter OC curve for a sampling plan. The conclusions are that performance measures should be selected relative to performance evaluation objectives and that graphs describing acceptance sampling plans for ideal inspectors should be modified to reflect performance of real inspectors under actual conditions.