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Introduction to Probability Models, Eighth Edition [Hardcover]

Sheldon M. Ross (Author)
3.6 out of 5 stars  See all reviews (20 customer reviews)


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Introduction to Probability Models, Tenth Edition Introduction to Probability Models, Tenth Edition 3.7 out of 5 stars (11)
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Book Description

January 3, 2003 0125980558 978-0125980555 8
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:
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

* Classic text by best-selling author
* Continues the tradition of expository excellence
* Contains compulsory material for Exam 3 of the
Society of Actuaries


Editorial Reviews

Review

"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

Book Description

Ross's bestseller--now updated with new material for actuarial exams and current applications in engineering, science, business, and economics --This text refers to an out of print or unavailable edition of this title.

Product Details

  • Hardcover: 775 pages
  • Publisher: Academic Press; 8 edition (January 3, 2003)
  • Language: English
  • ISBN-10: 0125980558
  • ISBN-13: 978-0125980555
  • Product Dimensions: 8.9 x 6.2 x 1.2 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 3.6 out of 5 stars  See all reviews (20 customer reviews)
  • Amazon Best Sellers Rank: #509,235 in Books (See Top 100 in Books)

 

Customer Reviews

20 Reviews
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Average Customer Review
3.6 out of 5 stars (20 customer reviews)
 
 
 
 
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15 of 18 people found the following review helpful:
3.0 out of 5 stars Good development of intuition, but not as good for other purposes..., September 27, 2006
This review is from: Introduction to Probability Models, Eighth Edition (Hardcover)
I have many of the same criticisms of this book that I do of Ross's book titled: "Probability: a first course". This book reviews most of the material from that book at a faster pace and then goes into other topics. Ross in the introduction states that his main goal in this text is to develop the reader's intuition for probabilistic reasoning. This book is excellent towards acheiving this goal, but not very good for anything else. It is a very "pure" probability text, completely ignoring the fact that the field of statistics exists and is useful. At the same time, it is somewhat weak on theory. Measure theory isn't mentioned, and the emphasis overall is on computation and problem solving, not proving theorems and understanding theoretical connections between different ideas.

This book has too many examples and not enough discussion. While the examples are usually well-executed, and while I think examples are important in probability, I think it's also important to talk about the abstract development of the subject. In my opinion, more prose and fewer examples would improve the quality of this text.

Another criticism I have of this book is that this book focuses exclusively on probability, refusing to touch statistics even with a ten foot pole. While this in itself is fine, I think this book misses numerous chances to pave the road towards the later study of mathematical statistics. The result is that someone reading this book will not be particularly well prepared for studying statistics, even though the fields of probability and statistics are intimately tied to each other.

Lastly, this book has gone through too many editions--one of the reasons I rated it 3 stars instead of 4 is that I believe that there has been almost no noticeable improvement in the last two editions (I have not read any farther back than that so I can't say more). I think this is a money-making scheme on behalf of the publisher, and I think this reflects poorly on the author and publisher alike.
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6 of 6 people found the following review helpful:
5.0 out of 5 stars very good, November 13, 2006
This review is from: Introduction to Probability Models, Eighth Edition (Hardcover)
I used this book for a graduate-level course in Stochastic Processes taught by Dr. Sheldon Ross himself. I must say that I never liked probability and stochastics until I read this book. Reading it is a pleasure! The topics are presented in a highly methodical manner, with plenty of examples and exercises. The exercises are presented in a gradation. Covers a wide range of topics, and is very helpful for a course in stochastics, especially for a student who doesn't have a strong background in P & SP. This is the book to own, don't miss it!
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17 of 22 people found the following review helpful:
2.0 out of 5 stars perfunctory treatment of stochastic processes, March 29, 2005
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This review is from: Introduction to Probability Models, Eighth Edition (Hardcover)
Tries to do too much and fails in delivering a rigorous understanding of the subject and this utter lack of mathematical rigor is the main flaw of the book. For a better understanding of stochastic processes consult the books by Karlin, Hoel and so forth. However, it does have some nice problems and some good examples to work through. I think that the author's other book, "A first course in probability" is much better.
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Inside This Book (learn more)
First Sentence:
Any realistic model of a real-world phenomenon must take into account the possibility of randomness. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
independent exponentials with rate, random telegraph signal process, tomorrow with probability, service with server, exponential random variables having mean, exponential with rate, process having rate, conditional variance formula, minimal path sets, renewal reward processes, arbitrage theorem, exponential random variable with rate, limiting probabilities, independent exponential random variables, single repairman, arrival theorem, interarrival distribution, elementary renewal theorem, nth event, preceding yields, distributed exponential random variables, exponentially distributed time, minimal cut sets, alternating renewal process, preceding gives
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, John Wiley, Second Edition, State Rate, Academic Press, Consider Example, Monte Carlo, Bonus Malus, Proof Let, First Course, New Jersey, Use the Martingale, Prentice Hall, Repeat Exercise, State Interpretation, Time Figure
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