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Independence

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Probability Theory

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 of σ(X i ), will be shown in Section 2 to concern only the joint distribution functions.

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References

  • O. Barndorff-Nielsen, “On the rate of growth of the partial maxima of a sequence of independent, identically distributed random variables,” Math. Scand. 9 (1961), 383–394.

    MathSciNet  MATH  Google Scholar 

  • F. Cantelli, “Su due applicazioni di un teorema di G. Boole, ”Rend. Accad. Naz. Lincei 26 (1917).

    Google Scholar 

  • K. L. Chung, “ The strong law of large numbers, ” Proc. 2nd Berkeley Symp. Stat, and Prob. (1951), 341–352.

    Google Scholar 

  • K. L. Chung, Elementary Probability Theory with Stochastic Processes, Springer-Verlag, Berlin, New York, 1974.

    MATH  Google Scholar 

  • J. L. Doob, Stochastic Processes, Wiley, New York, 1953.

    MATH  Google Scholar 

  • W. Feller, An Introduction to Probability Theory and Its Applications, Vol. 1, 3rd ed., Wiley, New York, 1950.

    MATH  Google Scholar 

  • A. Kolmogorov, Foundations of Probability, (Nathan Morrison, translator), Chelsea, New York, 1950.

    Google Scholar 

  • P. Lévy, Théorie de l’addition des variables aléatoires, Gauthier-Villars, Paris, 1937; 2nd ed., 1954.

    MATH  Google Scholar 

  • M. Loève, Probability Theory, 3rd ed. Van Nostrand, Princeton, 1963; 4th ed., SpringerVerlag, Berlin and New York, 1977–1978.

    MATH  Google Scholar 

  • R. von Mises, “Uber aufteilungs und Besetzungs Wahrscheinlichkeiten, ” Revue de la Faculté des Sciences de TUniversité dTstanbul, N.S. 4 (1939), 145–163.

    Google Scholar 

  • A. Renyi, Foundations of Probability, Holden-Day, San Francisco, 1970

    MATH  Google Scholar 

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© 1978 Springer-Verlag New York Inc.

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Chow, Y.S., Teicher, H. (1978). Independence. In: Probability Theory. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-0062-5_3

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  • DOI: https://doi.org/10.1007/978-1-4684-0062-5_3

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4684-0064-9

  • Online ISBN: 978-1-4684-0062-5

  • eBook Packages: Springer Book Archive

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