Introduction to Probability Models

Introduction to Probability Models

3.96 (148 ratings by Goodreads)
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"Introduction to Probability Models, 8th Edition", continues to introduce and inspire readers to the art of applying probability theory to phenomena in fields such as engineering, computer science, management and actuarial science, the physical and social sciences, and operations research. Now revised and updated, this best-selling book retains its hallmark intuitive, lively writing style, captivating introduction to applications from diverse disciplines, and plentiful exercises and worked-out examples. The 8th Edition includes five new sections and numerous new examples and exercises, many of which focus on strategies applicable in risk industries such as insurance or actuarial work. The five new sections include: Section 3.6.4 presents an elementary approach, using only conditional expectation, for computing the expected time until a sequence of independent and identically distributed random variables produce a specified pattern; Section 3.6.5 derives an identity involving compound Poisson random variables and then uses it to obtain an elegant recursive formula for the probabilities of compound Poisson random variables whose incremental increases are nonnegative and integer valued; Section 5.
4.3 is concerned with a conditional Poisson process, a type of process that is widely applicable in the risk industries; Section 7.10 presents a derivation of and a new characterization for the classical insurance ruin probability; Section 11.8 presents a simulation procedure known as coupling from the past; its use enables one to exactly generate the value of a random variable whose distribution is that of the stationary distribution of a given Markov chain, even in cases where the stationary distribution cannot itself be explicitly determined. Other Academic Press books by Sheldon Ross include: "Simulation 3rd Ed.", ISBN:0-12-598053-1, "Probability Models for Computer Science", ISBN 0-12-598051-5, "Introduction to Probability and Statistics for Engineers and Scientists, 2nd Ed.", ISBN: 0-12-598472-3. This is a classic text by best-selling author. It continues the tradition of expository excellence. It contains compulsory material for Exam 3 of the Society of Actuaries.
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Product details

  • Audio | 775 pages
  • 157.48 x 226.06 x 30.48mm | 1,065.94g
  • Academic Press Inc
  • San Diego, United States
  • Revised
  • 8th Revised edition
  • illustrations, index
  • 0125980558
  • 9780125980555

Table of contents

Preface; 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; Simulation; Appendix: Solutions to Starred Exercises; Index
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Review quote

"The strength of the book is that it overviews quite a number of disciplines. It is perfect for actuaries...This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book". Jean Lemaire, University of Pennsylvania, Wharton School "The examples, like the exercises are great. Ross mixes elementary examples to illustrate concept and formula basics with advanced examples pulled from every imaginable discipline." Matt Carlton, California Polytechnic State University
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About Sheldon M. Ross

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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148 ratings
3.96 out of 5 stars
5 35% (52)
4 38% (56)
3 20% (30)
2 2% (3)
1 5% (7)
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