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Independence

  • Yuan Shih Chow
  • Henry Teicher
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

Independence may be considered the single most important concept in probability theory, demarcating the latter from measure theory and fostering an independent development. In the course of this evolution, probability theory has been fortified by its links with the real world, and indeed the definition of independence is the abstract counterpart of a highly intuitive and empirical notion. Independence of random variables {X i}, the definition of which involves the events ofσ(X i) will be shown in Section 2 to concern only the joint distribution functions.

Keywords

Success Probability Independent Random Variable Bernoulli Trial Joint Distribution Function Independent Classis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York Inc. 1988

Authors and Affiliations

  • Yuan Shih Chow
    • 1
  • Henry Teicher
    • 2
  1. 1.Department of Mathematical StatisticsColumbia UniversityNew YorkUSA
  2. 2.Department of StatisticsRutgers UniversityNew BrunswickUSA

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