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Theory and Examples

4th Edition

$88.00 (P)

Part of Cambridge Series in Statistical and Probabilistic Mathematics

  • Date Published: August 2010
  • availability: Available
  • format: Hardback
  • isbn: 9780521765398

$ 88.00 (P)

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About the Authors
  • This book is an introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems.

    • More than 250 good examples and 500 exercises
    • Comprehensive treatment in only 400 pages
    • Concentrates on results useful for application
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    Reviews & endorsements

    "This book is also an excellent resource. Several interesting and concrete examples are presented throughout the textbook, which will help novices obtain a better understanding of the fundamentals of probability theory."
    Ramesh Garimella, Computing Reviews

    "The best feature of the book is its selection of examples. The author has done an extraordinary job in showing not simply what the presented theorems can be used for, but also what they cannot be used for."
    Miklos Bona, SIGACT News

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    Product details

    • Edition: 4th Edition
    • Date Published: August 2010
    • format: Hardback
    • isbn: 9780521765398
    • length: 440 pages
    • dimensions: 257 x 185 x 30 mm
    • weight: 0.96kg
    • contains: 23 b/w illus. 532 exercises
    • availability: Available
  • Table of Contents

    1. Measure theory
    2. Laws of large numbers
    3. Central limit theorems
    4. Random walks
    5. Martingales
    6. Markov chains
    7. Ergodic theorems
    8. Brownian motion
    Appendix A. Measure theory details.

  • Instructors have used or reviewed this title for the following courses

    • Graduate Probability
    • Probability Math
    • Quantitative analaysis
  • Author

    Rick Durrett, Duke University, North Carolina
    Rick Durrett received his PhD in Operations Research from Stanford University in 1976. After nine years at UCLA and twenty-five at Cornell University, he moved to Duke University in 2010, where he is a Professor of Mathematics. He is the author of eight books and more than 170 journal articles on a wide variety of topics, and he has supervised more than 40 PhD students. He is a member of the National Academy of Science and the American Academy of Arts and Sciences and a Fellow of the Institute of Mathematical Statistics.

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