Introduction to Probability Models, 11th Edition

ABOUT THIS BOOK
Sheldon 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 introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research.

The hallmark features of this renowned text remain in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics. The 65% new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data.


TABLE OF CONTENTS
Preface
Introduction to Probability Theory
Random Variables
Conditional Probability and Conditional Expectation
Markov Chains
The Exponential Distribution and the Poisson Process
Continuous-Time Markov Chains
Renewal Theory and Its Applications
Queueing Theory
Reliability Theory
Brownian Motion and Stationary Processes
Simulation
Appendix: Solutions to Starred Exercises
Index