Introduction to Probability Models – Sheldon M. Ross – 6th Edition


The Sixth Edition of this very successful textbook; Introduction to Models; introduces elementary probability theory and stochastic processes. This is particularly well-suited for those who want to see how probability theory can be applied to the study of phenomena in fields such as engineering; management science; the physical and social sciences; and operations research.

The Sixth Edition includes additional exercises in every chapter and a new appendix with the answers to approximately 100 of the included exercises from throughout the text. Markov Chain Monte Carlo methods are presented in an entirely new section; along with new coverage of the Markov Chain cover times. New material will also be featured on K-records values and Ignatov’s theorem. This is a worthwhile revision of Ross’s classic text.

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Table of Contents

Introduction to Probability Theory
Random Variables
Conditional Probability and Conditional Expectation
Markov Chains
The Exponential Distribution and the Poisson Process
Continuous-Time Markov Chains
Renewal Theory and Its Applications
Queueing Theory
Reliability Theory
Brownian Motion and Stationary Processes

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