Bayesian Evaluation of Inspectors in Sensory Tests

Abstract

This paper examines a Bayesian rule recently suggested for the classification of inspectors in sensory tests. The rule is presented and shown to be equivalent to a Bayesian hypothesis testing procedure, which aids in the interpretation of the rule. The rule is then improved upon by making fuller use of available sample data. Finally, an extension to the case of unknown error probabilities within inspector classes is briefly described.

• Bayesian Classification Rule
• Bayesian Hypothesis Testing
• Decision Theory
• Sensory Tests

Additional information

Notes on contributors

Christopher B. Barry

Dr. Barry is President of Micro Data Base Systems, Inc. He was an Associate Professor of Finance in the Graduate School of Business at the University of Texas at Austin when this article was written.