Introduction to Probability Models book cover

Introduction to Probability Models

Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries.

Ancillary list:

  • Instructor's Manual - http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123743886
  • Student Solutions Manual - http://www.elsevierdirect.com/product.jsp?isbn=9780123756862#42
  • Sample Chapter, eBook - http://www.elsevierdirect.com/product.jsp?isbn=9780123756862

Audience
Professionals and students in actuarial science, engineering, operations research, and other fields in applied probability.

Hardbound, 800 Pages

Published: December 2009

Imprint: Academic Press

ISBN: 978-0-12-375686-2

Reviews

  • Praise from Reviewers: “I think Ross has done an admirable job of covering the breadth of applied probability. Ross writes fantastic problems which really force the students to think divergently...The examples, like the exercises are great.” - Matt Carlton, California Polytechnic Institute “This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book." - Jean LeMaire, University of Pennsylvania “This book may be a model in the organization of the education process. I would definitely rate this text to be the best probability models book at its level of difficulty...far more sophisticated and deliberate than its competitors.” - Kris Ostaszewski, University of Illinois

Contents

  • Preface

    1. Introduction to Probability Theory;
    2. Random Variables
    3. Conditional Probability and Conditional Expectation
    4. Markov Chains
    5. The Exponential Distribution and the Poisson Process
    6. Continuous-Time Markov Chains
    7. Renewal Theory and Its Applications
    8. Queueing Theory
    9. Reliability Theory
    10. Brownian Motion and Stationary Processes
    11. Simulation

    Appendix: Solutions to Starred Exercises
    Index

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