An Application of Fuzzy Set Theory to Statistical Hypothesis Testing.

Abstract

In many instances the data used in statistical hypothesis testing may be vague or imprecise and, as such, may suggest results that are incorrect. Rank tests, in particular, seem susceptible, since the original data, once ranked, have no further influence on the testing procedure no matter how closely they are grouped. A possible solution is to treat the ranks as fuzzy integers represented by membership functions that indicate the degree to which each rank assumes each integer value. In this paper, a method is suggested for obtaining these membership functions; and the concept is incorporated into an existing rank test. An application of this fuzzy hypothesis testing procedure is provided. Keywords: Fuzzy ranking; Probability; Permutations; Kill probabilities.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1987
Accession Number
ADA186705

Entities

People

  • William E. Baker

Organizations

  • Ballistic Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Ground and Sea Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Army
  • Computer Science
  • Computer Simulations
  • Computers
  • Data Analysis
  • Data Sets
  • Fuzzy Sets
  • Marine Corps
  • Military Research
  • Munitions
  • Security
  • Set Theory
  • Simulations
  • United States
  • Universities
  • Weapons

Fields of Study

  • Mathematics

Readers

  • Artificial Intelligence
  • Regression Analysis.