Introduction to Probability Models: Thirteenth Edition is available in two manageable volumes: an Elementary edition appropriate for undergraduate use and an Advanced edition for graduate use. Together, and through their hallmark exercises and real examples, both versions offer a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Users will find comprehensive information that introduces them to the foundations of probability modeling and stochastic processes from Random Variables, to Markov Chains and Renewal Theory.
1. 1. Introduction to Probability Theory - p. 1 2. 2. Random Variables - p. 23 3. 3. Conditional Probability and Conditional Expectation - p. 103 4. 4. Markov Chains - p. 201 5. 5. The Exponential Distribution and the Poisson Process - p. 301 6. 6. Continuous-Time Markov Chains - p. 383 7. 7. Renewal Theory and Its Applications - p. 439 8. 8. Queueing Theory - p. 519 9. 9. Reliability Theory - p. 603 10. 10. Brownian Motion and Stationary Processes - p. 653 11. 11. Simulation - p. 693 12. 12. Coupling - p. 757 13. 13. Martingales - p. 787 14. Solutions to Starred Exercises - p. 799 15. Index - p. 843
Introduction to Probability Models: Thirteenth Edition is available in two manageable volumes: an Elementary edition appropriate for undergraduate use and an Advanced edition for graduate use. Together, and through their hallmark exercises and real examples, both versions offer a comprehensive foundation of this key subject with applications across engineering, computer science, management science, the physical and social sciences and operations research. Users will find comprehensive information that introduces them to the foundations of probability modeling and stochastic processes from Random Variables, to Markov Chains and Renewal Theory.
1. 1. Introduction to Probability Theory - p. 1 2. 2. Random Variables - p. 23 3. 3. Conditional Probability and Conditional Expectation - p. 103 4. 4. Markov Chains - p. 201 5. 5. The Exponential Distribution and the Poisson Process - p. 301 6. 6. Continuous-Time Markov Chains - p. 383 7. 7. Renewal Theory and Its Applications - p. 439 8. 8. Queueing Theory - p. 519 9. 9. Reliability Theory - p. 603 10. 10. Brownian Motion and Stationary Processes - p. 653 11. 11. Simulation - p. 693 12. 12. Coupling - p. 757 13. 13. Martingales - p. 787 14. Solutions to Starred Exercises - p. 799 15. Index - p. 843
