A DECISION THEORY APPROACH TO ACCEPTANCE TESTING

Abstract

The report discusses the application of statistical decision theory to the problem of acceptance testing by attributes. The classical approach to acceptance testing is introduced and discussed so that it may be contrasted with the decision theory approach. The decision theory approach, which attempts to find an optimal trade-off between the expected costs of wrong decisions and sampling costs, is illustrated by an example using the Bayesian statistical viewpoint. In the example, sample size is assumed to be predetermined and the problem is to select the optimal action based upon prior knowledge and the results of the sample inspection. The problem is then broadened to include the trade-off between the costs of wrong decisions and the costs of sampling inspection. A numerical example is solved via a simple computer program to illustrate the results of the analysis. A survey of the literature dealing with the application of decision theory to acceptance testing is presented, the contents of the report discussed, and suggestions for further work made.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 1968
Accession Number
AD0665029

Entities

People

  • C. E. Wisler
  • E. D. Simmons

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Bayes Theorem
  • Classification
  • Computer Programs
  • Computers
  • Data Science
  • Decision Theory
  • Experimental Data
  • Inspection
  • Literature
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Sampling
  • Statistical Decision Theory
  • Statistics
  • Surveys

Fields of Study

  • Mathematics

Readers

  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms