Introduction To Probability Models

Hardcover | January 22, 2014

bySheldon M. RossEditorSheldon M. Ross

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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. Updated data, and a list of commonly used notations and equations, instructor's solutions manual Offers new applications of probability models in biology and new material on Point Processes, including the Hawkes process Introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences, and operations research Covers finite capacity queues, insurance risk models, and Markov chains Contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams Appropriate for a full year course, this book is written under the assumption that students are familiar with calculus

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From the Publisher

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 engineer...

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A...

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Format:HardcoverDimensions:784 pages, 9.41 × 7.24 × 0.98 inPublished:January 22, 2014Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0124079482

ISBN - 13:9780124079489

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Extra Content

Table of 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

Editorial Reviews

Praise from Reviewers:"This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book."- Jean LeMaire, University of Pennsylvania"I think Ross has done an admirable job of covering the breadth of applied probability. Rosswrites fantastic problems which really force the students to think divergently...The examples, like the exercises are great.?- Matt Carlton, Cal Polytechnic Institute"This book may be a model in the organization of the education process. I would definitely ratethis 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