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Introduction to Probability Models, Eleventh Edition, by Sheldon M. Ross
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Sheldon Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research.
The hallmark features of this renowned text remain in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics. The 65% new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data.
- Updated data, and a list of commonly used notations and equations, instructor's solutions manual
- Offers new applications of probability models in biology and new material on Point Processes, including the Hawkes process
- Introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences, and operations research
- Covers finite capacity queues, insurance risk models, and Markov chains
- Contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams
- Appropriate for a full year course, this book is written under the assumption that students are familiar with calculus
- Sales Rank: #59286 in Books
- Published on: 2014-02-05
- Original language: English
- Number of items: 1
- Dimensions: 9.02" h x 1.63" w x 5.98" l, 2.50 pounds
- Binding: Hardcover
- 784 pages
Review
"The hallmark features of this renowned text remain in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics…new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data."--Zentralblatt MATH 1284-1 "…the newest edition updated with new examples and exercises, actuarial material, Hawkes and other point processes, Brownian motion, and expanded coverage of Markov chains. Although formally rigorous, the emphasis is on helping students to develop an intuitive sense for probabilistic thinking."--ProtoView.com, April 2014 Praise from Reviewers for the 10th edition:
"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, California Polytechnic Institute "This is a fascinating introduction to applications from a variety of disciplines. Any curious student will love this book."--Jean LeMaire, University of Pennsylvania "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
About 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.
Most helpful customer reviews
5 of 5 people found the following review helpful.
Good mathematical treatment of probability applications. "Mathematical maturity" strongly suggested.
By Yeng C.
This is a text written at an undergraduate level which assumes an excellent background in undergraduate probability (i.e., probability density functions, transformations of random variables, etc.) and some familiarity with matrix algebra. If you don't like mathematical equations, derivations and proofs using algebraic manipulation, you will hate this book. The book is written more like a manual of methods and their justifications; do not expect the author to hold your hand throughout every step in every derivation. Extremely comprehensive and very useful for anyone serious about studying probability.
7 of 10 people found the following review helpful.
Not as good as its reputation
By Turtleman
This book is known to be one of the best textbooks available on the market.
However, I think the reputation is exaggerated.
Overall, the shortcomings of this book are
1.
There are LOTS of examples....
However, each example uses different approach, so it is hard to see any logical similarities between examples.
I felt that too many examples were randomly thrown to reader.
2.
Absolutely no figure over entire book. No state diagram, probability distribution plot, or anything.
3.
It book is excellent until Ch 4 (Markov Chain), explain in very clear words with many examples.
Then, something strange happens: it starts to use more and more abstract variables and less and less examples.
Further, most examples in later part are either derivation or generalization of theorem.
On the other hand, the strength of the book is the end-of-chapter problems.
Those problems are all engineering-style practical problems.
IF(!) you have solutions manual, this book is THE BEST book to learn stochastic process.
0 of 0 people found the following review helpful.
Sheldon Ross makes learning probability interesting, challenging, and rewarding.
By John Featherstone
If you are interested in learning probability and stochastic processes, Ross is excellent. Enough said.
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