Introduction to Probability Models (Google eBook)

Front Cover
Academic Press, Dec 11, 2006 - Mathematics - 800 pages
3 Reviews

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 -
  • Student Solutions Manual -
  • Sample Chapter, eBook -

New to this Edition:

  • 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains
  • Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams
  • Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, test bank, and companion website
  • Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field

Hallmark features:

  • Superior writing style
  • Excellent exercises and examples covering the wide breadth of coverage of probability topics
  • Real-world applications in engineering, science, business and economics

What people are saying - Write a review

Review: Introduction to Probability Models

User Review  - Jette Stuart - Goodreads

Sheldon Ross is a genius of our time. This is an excellent book for introduction to stochastic processes, a subject that I am sure most find challenging. Read full review

Review: Introduction to Probability Models

User Review  - Mohamed Al-Emam - Goodreads

college related Read full review


Chapter 3 Conditional Probability and Conditional Expectation
Chapter 4 Markov Chains
Chapter 5 The Exponential Distribution and the Poisson Process
Chapter 6 ContinuousTime Markov Chains
Chapter 7 Renewal Theory and Its Applications
Chapter 8 Queueing Theory
Chapter 9 Reliability Theory
Chapter 10 Brownian Motion and Stationary Processes
Chapter 11 Simulation
Solutions to Starred Exercises

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About the author (2006)

Sheldon M. Ross is the Epstein Chair Professor at the Department of Industrial and Systems Engineering, University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968 and was formerly a Professor at the University of California, Berkeley, from 1976 until 2004. He has published more than 100 articles and a variety of textbooks in the areas of statistics and applied probability, including Topics in Finite and Discrete Mathematics (2000), Introduction to Probability and Statistics for Engineers and Scientists, Fourth Edition (2009), A First Course in Probability, Eighth Edition (2009), and Introduction to Probability Models, Tenth Edition (2009), among others. Dr Ross serves as the editor for Probability in the Engineering and Informational Sciences.

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