ABSTRACT
This chapter presents methods for estimating the rate of nonconformities based on a sample of size n. The sample may consist of n separate items, each of which may have one or more nonconformities, or it may consist of a continuous sample of n units. Point estimates and interval estimates are described, using both the classical maximum likelihood approach and a Bayesian approach. The chapter illustrates methods for incorporating prior knowledge into the analysis and shows that the resulting estimates are usually more precise than those based solely on the current sample.
