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December 1, 1984Journal of the American Statistical Association16,377 citationsOpen Access

Probability, Random Variables, and Stochastic Processes.

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JAJulia AbrahamsAPA. Papoulis

Key Points

  • To provide a detailed understanding of probability concepts, random variables, and stochastic processes.
  • Structured in two parts: Probability and Random Variables, Stochastic Processes.
  • Each section covers essential concepts and their applications.
  • Includes theoretical foundations and practical examples.
  • Foundational principles of probability are established through axioms and repeated trials.
  • Random variables and their functions are examined in detail.
  • Stochastic processes, including Markov chains and queueing theory, are explored for real-world applications.

Abstract

Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing Theory

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Cite This Study

Abrahams et al. (1984) studied this question.

synapsesocial.com/papers/69ee775a7beaa90d72fab991https://doi.org/10.2307/2288754
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