Introduction to Probability Models, 11th Edition

Release Date: 22 Jan 2014

Imprint: Academic Press

Print Book ISBN : 9780124079489

eBook ISBN : 9780124081215

Pages: 784

Dimensions: 229 X 152

Sheldon Ross's classic bestseller, now in its 11th edition, is the leading market text for advanced undergraduates taking Introduction to Probability, a course taught at all major colleges and universities throughout the world.

Introduction to Probability Models, 11th Edition

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

Key Features

• 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

Description

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.

Readership

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

Sheldon Ross

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 First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

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