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


Sheldon Ross’s classic bestseller, Introduction to Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied . It introduces elementary theory and stochastic , and shows how theory can be applied fields such as , computer , science, the and social sciences, and operations research.

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 solutions manual
  • Offers new applications of probability models in biology and new material on Point Processes, including the Hawkes
  • 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 is written under the assumption that are familiar with

Table of Content

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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