Chapter 1. Introduction to Probability Theory -- Chapter 2. Random Variables -- Chapter 3. Conditional Probability and Conditional Expectation -- Chapter 4. Markov Chains -- Chapter 5. The Exponential Distribution and the Poisson Process -- Chapter 6. Continuous-Time Markov Chains -- Chapter 7. Renewal Theory and Its Applications -- Chapter 8. Queueing Theory -- Chapter 9. Reliability Theory -- Chapter 10. Brownian Motion and Stationary Processes -- Chapter 11. Simulation -- Chapter 12. Coupling.
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SUMMARY OR ABSTRACT
Text of Note
Introduction to Probability Models, Twelfth Edition, is the latest version of Sheldon Ross's classic bestseller. This trusted book introduces the reader to elementary probability modelling 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. The hallmark features of this text have been retained in this edition, including a superior writing style and excellent exercises and examples covering the wide breadth of coverage of probability topics. In addition, many real-world applications in engineering, science, business and economics are included.