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Probability and Statistics by Example

Probability and Statistics by Example

Probability and Statistics by Example

Volume 2: Markov Chains: A Primer in Random Processes and their Applications
Yuri Suhov , University of Cambridge
Mark Kelbert , University of Wales, Swansea
June 2008
2. Markov Chains: A Primer in Random Processes and their Applications
Available
Paperback
9780521612340

    Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science and engineering, the authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises with complete solutions, adapted to needs and skills of students. Following on from the success of Probability and Statistics by Example: Basic Probability and Statistics, the authors here concentrate on random processes, particularly Markov processes, emphasizing models rather than general constructions. Basic mathematical facts are supplied as and when they are needed and historical information is sprinkled throughout.

    • Enables readers to develop effective techniques for learning about and developing a deeper understanding of probability and statistics
    • Contains a substantial number of Cambridge exam questions, and solutions to help students prepare for examinations
    • Will also aid students from other disciplines such as engineering and social sciences - and those who need a background in random processes for careers in finance, insurance, actuarial studies and economics

    Reviews & endorsements

    "I enjoyed reading this book a great deal... it is a great way to flesh out the general theory with concrete examples and applications."
    Darren Glass, MAA Reviews

    "In this book one can find a well-balanced mix of clearly explained theory, several classical and interesting examples which complement and integrate the theory discussed as well we though-provoking quotations and humorous sentences which make reading this book very pleasant."
    Emanuele Taufer, Mathematical Reviews

    "... I did enjoy browsing through this somewhat baroque book."
    Rudolf Gruebel, The American Statistician

    See more reviews

    Product details

    July 2008
    Hardback
    9780521847674
    498 pages
    250 × 180 × 25 mm
    1.14kg
    151 b/w illus.
    Available

    Table of Contents

    • Preface
    • Introduction: Andrei Markov and his time
    • 1. Discrete-time Markov chains
    • 2. Continuous-time Markov chains: basic theory
    • 3. Statistics of discrete-time Markov chains
    • Afterword: Pearson, Maxwell and other famous Cambridge Wranglers of the past: some lessons to be learned
    • Bibliography
    • Appendix
    • Index.
    Resources for
    Type
      Authors
    • Yuri Suhov , University of Cambridge

      Yuri Suhov is a Professor of Applied Probability in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge.

    • Mark Kelbert , University of Wales, Swansea

      Mark Kelbert is a Reader in Statistics in the Department of Mathematics at Swansea University. For many years he has also been associated with the Moscow Institute of Information Transmission Problems and the International Institute of Earthquake Prediction Theory and Mathematical Geophysics (Moscow).