Introduction to Probability Models – Sheldon M. Ross – 9th Edition

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 . It introduces elementary probability theory and , and shows how probability theory can be applied such as engineering, computer , management science, the and , and .

The hallmark features of this renowned text remain in this 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
  • Offers new applications of probability models in 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 are familiar with calculus
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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

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