BIASED SAMPLING; THE NONCENTRAL HYPERGEOMETRIC PROBABILITY DISTRIBUTION

Abstract

Consider a set S of L elements which is dichotomized in some manner (say, by an observable characteristic) into subsets M and N containing m and n = L - m elements, respectively, and a sampling mechanism which in some way selects a subset R of r elements from S. Let a be a realization of the random variable A denoting the number of elements in R arc of circle M. The hypothesis that the sampling mechanism is random is tested against the alternative of "non-randomness."

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Document Details

Document Type
Technical Report
Publication Date
Nov 29, 1963
Accession Number
AD0426243

Entities

People

  • Kenneth T. Wallenius

Organizations

  • Stanford University

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Facilities
  • Business Administration
  • Difference Equations
  • Differential Equations
  • Engineering
  • Geography
  • Integrals
  • Jet Propulsion
  • Munitions
  • National Security
  • New Jersey
  • New York
  • Operations Research
  • Ordnance Laboratories
  • Probability
  • Probability Distributions
  • Random Variables

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Structural Dynamics.