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Introduction to Probability Models / Edition 10

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Overview

Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professors as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. The tenth edition contains several sections covered in the new exams.

Features

Writing style, exercises, and examples help students to "think probabilistically"

Contains everything one might want to know about probability models, making it a great reference

New topic coverage including:

finite capacity queues

insurance risk models

skip free random walks to model one's successive fortune in a sequence of gambling games in which one is always betting the same amount

simulating stationary distributions of Markov chains

"...introduces elementary probability theory & stochastic processes...shows applications for engineering, the physical & social sciences, and operations research...features new material on K-records values & Ignatov's theorem.

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Editorial Reviews

From the Publisher
Praise from Reviewers:
“This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book."
- Jean LeMaire, University of Pennsylvania
“I think Ross has done an admirable job of covering the breadth of applied probability. Ross writes fantastic problems which really force the students to think divergently...The examples, like the exercises are great.”
- Matt Carlton, Cal Polytechnic Institute
“This book may be a model in the organization of the education process. I would definitely rate this text to be the best probability models book at its level of difficulty...far more sophisticated and deliberate than its competitors.”
- Kris Ostaszewski, University of Illinois
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Product Details

  • ISBN-13: 9780123756862
  • Publisher: Elsevier Science
  • Publication date: 12/3/2009
  • Edition number: 10
  • Pages: 784
  • Product dimensions: 6.20 (w) x 9.10 (h) x 1.40 (d)

Meet the Author

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

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Table of Contents

Preface to the Fifth Edition
Preface to the Sixth Edition
Preface to the Seventh Edition
1 Introduction to Probability Theory 1
2 Random Variables 23
3 Conditional Probability and Conditional Expectation 93
4 Markov Chains 163
5 The Exponential Distribution and the Poisson Process 241
6 Continuous-Time Markov Chains 313
7 Renewal Theory and Its Applications 363
8 Queueing Theory 427
9 Reliability Theory 499
10 Brownian Motion and Stationary Processes 549
11 Simulation 585
Appendix: Solutions to Starred Exercises 649
Index 687
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