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First Look at Rigorous Prob..(2nd Ed)

by Rosenthal Jeffrey S

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Probability theory through measure theory

$64.60 USD
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Hardcover New English

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AlbakiReads Editorial

Probability theory through measure theory

Jeffrey S. Rosenthal’s textbook introduces probability theory with measure theory as its foundation. It presents the mathematical details through probabilistic concepts and includes complete proofs of essential introductory results. The second edition adds exercises, expands existing material, and introduces several smaller topics. For a graduate student working outside mathematics, the book’s organizing principle is significant: measure theory is developed in connection with the probability it supports, rather than treated as a separate preliminary subject. The scope remains introductory, with an emphasis on precise arguments and a working command of the subject.

Good fit for readers who enjoy

  • Graduate students seeking a measure-theoretic introduction to probability
  • Students in statistics, finance, computer science, engineering, or related fields who need rigorous probability
  • Learners who want complete proofs and exercises

Themes

Probability theoryMeasure theoryMathematical proofsGraduate-level mathematics

Based on publisher information and book metadata.

Book overview

This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail.

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