Foundations of the Theory of Probability
Author: A. N. Kolmogorov
Added by: mirtitles
Added Date: 2021-12-14
Language: eng
Subjects: probability theory, soviet, mathematics, distributions, statistics, axioms, infinite dimensional spaces, integration with respect to parameter, bayes theorem, infinite probability fields, random variables, lebesgue integrals, expectation values, conditional probabilities, law of large numbers, independence, strong law of large numbers
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Description
The purpose of this monograph is to give an axiomatic foundation for the theory of probability. The author set himself the task of putting in their natural place, among the general notions of modern mathematics, the basic concepts of probability theory—concepts which until recently were considered to be quite peculiar.
This task would have been a rather hopeless one before the introduction of Lebesgue’s theories of measure and integration. However, after Lebesgue’s publication of his investigations, the analogies between measure of a set and probability of an event, and between integral of a function and mathematical expectation of a random variable, became apparent. These analogies allowed of further extensions; thus, for example, various properties of independent random variables were seen to be in complete analogy with the corresponding properties of orthogonal functions. But if probability theory was to be based on the above analogies, it still was necessary to make the theories of measure and integra tion independent of the geometric elements which were in the foreground with Lebesgue. This has been done by Frechet.
While a conception of probability theory based on the above general viewpoints has been current for some time among certain mathematicians, there was lacking a complete exposition of the whole system, free of extraneous complications.
I wish to call attention to those points of the present exposition which are outside the above-mentioned range of ideas familiar to the specialist. They are the following: Probability distributions in infinite-dimensional spaces (Chapter III, § 4) ; differentiation and integration of mathematical expectations with respect to a parameter (Chapter IV, § 5) ; and especially the theory of condi tional probabilities and conditional expectations (Chapter V). It should be emphasized that these new problems arose, of necessity, from some perfectly concrete physical problems.
The sixth chapter contains a survey, without proofs, of some results of A. Khinchine and the author of the limitations on the applicability of the ordinary and of the strong law of large num bers. The bibliography contains some recent works which should be of interest from the point of view of the foundations of the subject.