Introduction to Probability Models, Seventh Edition [Hardcover]

Sheldon M. Ross (Author)

Book Description

Publication Date: February 18, 2000 | ISBN-10: 0125984758 | ISBN-13: 978-0125984751 | Edition: 7

The seventh edition of the successful Introduction to Probability Models introduces elementary probability theory and the stochastic processes and is particularly well-suited to those applying probability theory to the study of phenomena in engineering, management science, the physical and social sciences, and operations research. Skillfully organized, Introduction to Probability Models covers all essential topics. Sheldon Ross, a talented and prolific textbook author, distinguishes this carefully and substantially revised book by his effort to develop in students an intuitive, and therefore lasting, grasp of probability theory. The seventh edition includes many new examples and exercises, with the majority of the new exercises being less demanding of the student. In addition, the text introduces stochastic processes, stressing applications, in an easily understood manner. There is a comprehensive introduction to the applied models of probability that stresses intuition. Both students and professors will agree that this is the most solid and widely used text for probability theory.


* Provides a detailed coverage of the Markov Chain Monte Carlo methods and Markov Chain covertimes
* Gives a thorough presentation of k-record values and the surprising Ignatov's theorem
* Includes examples relating to: "Random walks to circles," "The matching rounds problem," "The best prize problem" and many more
* Contains a comprehensive appendix with the answers to approximately 100 exercises from throughout the text
* Accompanied by a complete instructor's solutions manual with step-by-step solutions to all exercises
NEW TO THIS EDITION
* Includes many new and easier examples and exercises
* Offers new material on utilizing probabilistic method in combinatorial optimization problems
* Includes new material on suspended animation reliability models
* Contains new material on random algorithms and cycles of random permutations

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 --This text refers to an out of print or unavailable edition of this title.

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.

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Product Details

• Hardcover: 693 pages
• Publisher: Academic Press; 7 edition (February 18, 2000)
• Language: English
• ISBN-10: 0125984758
• ISBN-13: 978-0125984751
• Product Dimensions: 9 x 5.9 x 1.5 inches
• Shipping Weight: 2.2 pounds
• Average Customer Review: 3.8 out of 5 stars  See all reviews (6 customer reviews)
• Amazon Best Sellers Rank: #838,695 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

49 of 50 people found the following review helpful:

5.0 out of 5 stars I love this book!, September 14, 2000

By 

Todd Ebert (Long Beach California) - See all my reviews

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This review is from: Introduction to Probability Models, Seventh Edition (Hardcover)

The first four chapters alone (intro, random variables, conditonal probability, markov chains) are worth the price of the book. The author packs each chapter with very interesting examples and problems. The one I found most interesting was his probabilistic analysis of the 2-SAT and SAT problems of computer science. Here he gives an informal math argument as to why 2-SAT is polynomial time decidable and why SAT should be intractable.

On the other hand, I think someone relatively new to probability theory may find his neat problems and examples a bit too much with a first reading. The book is in its seventh edition, and I think Ross has taken advantage of this by providing newer insights and more interesting problems, but in doing so it may overwhelm the novice.

If you are learning probability for the first or second time, I recommend you supplement this book with Roussas "A Course in Mathematical Statistics". Despite its title, the first 9 chapters give a calculus-based intro to probability. And the rest of the book is *excellent* for a calculus-based intro to statistics.

8 of 9 people found the following review helpful:

3.0 out of 5 stars Comprehensive and Complex, September 25, 2000

By A Customer

This review is from: Introduction to Probability Models, Seventh Edition (Hardcover)

This text really tests your ability to follow logic, summations and algebraic manipulation. Anyone without a sound knowledge of calculus may find some of the problems quite difficult. But the applications to many fields makes this book quite useful and worth the effort.

3 of 3 people found the following review helpful:

4.0 out of 5 stars better for introduction to stochastic, October 21, 2001

By 

"poiet_bilkent" (Turkey, Bilkent) - See all my reviews

This review is from: Introduction to Probability Models, Seventh Edition (Hardcover)

Especially for the students of industrial engineering may use this book after taking a course about probability. It is an introduction to stochastic processing book and really good for the subjects of Markov Chains and Poisson Process. There is a small part in the book about stochastic modelling and simulation. Be careful that the proofs are not very well and the questions are a bit easy but time consuming. Beside those, do not forget: this is not an introduction to probability but probability models; where some probability knowledge is needed.