In this study, performance of single acceptance sampling plans by attribute is investigated by using the distribution of fraction nonconformance (i.e., lot quality distribution (LQD)) for a dependent production process. It is the aim of this study to demonstrate that, in order to emphasize consumer risk (i.e., the risk of accepting a bad lot), it is better to evaluate a sampling plan based upon its performance as assessed by the posterior distribution of fractions nonconforming in accepted lots. Similarly, it is the desired posterior distribution that sets the basis for designing a sampling plan. The prior distribution used in this study is derived from a Markovian model of dependence.

Publication Date



This is an Accepted Manuscript of an article published by Taylor & Francis in the Journal of Applied Statistics on January 21, 2010, available online: https://doi.org/10.1080/02664760902998451

Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type


Department, Program, or Center

Accounting (SCB)


RIT – Main Campus