Bayesian Analysis of Quality Level Using Simulation Methods

Abstract

This article demonstrates how Bayesian methods for making inferences about the number, or proportion, of nonconforming units in a quality control setting can be implemented using simulation techniques. Random draws from the posterior distribution of the target quantities of interest are used to construct the needed inferences. The same random draws from the posterior distribution are also used to perform model checking and sensitivity analysis. The methods are illustrated using two examples. The methods can be generalized to more complicated situations which are illustrated by discussing the extensions of both the examples.

• Acceptance Sampling
• Bayesian Methods
• Posterior Distribution
• Quality Control
• Sensitivity Analysis
• Variable Sampling

Additional information

Notes on contributors

T. E. Raghunathan

Dr. Raghunathan is an Associate Professor of Biostatistics and a Senior Associate Research Scientist at the Institute for Social Research. His email address is [email protected].