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Introduction to Probability Models

Introduction to Probability Models [Kindle Edition]

Sheldon M. Ross
5.0 out of 5 stars  See all reviews (1 customer review)

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Praise from Reviewers: "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

Product Description

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 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.

New to this Edition:

  • 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains
  • Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams
  • Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, test bank, and companion website
  • Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field

Hallmark features:

  • Superior writing style
  • Excellent exercises and examples covering the wide breadth of coverage of probability topics
  • Real-world applications in engineering, science, business and economics

Product details

  • Format: Kindle Edition
  • File Size: 8147 KB
  • Print Length: 800 pages
  • Publisher: Academic Press; 10 edition (11 Dec 2006)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B004EYSPP0
  • Text-to-Speech: Enabled
  • X-Ray:
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Bestsellers Rank: #788,540 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews
2 of 2 people found the following review helpful
5.0 out of 5 stars Just started studying the book! 15 Aug 2013
Format:Hardcover|Verified Purchase
However in a preliminary skim read it looks perfect to prepare, in a self study fashion, a fair amount of material for the "Royal Statistical Society" exams.

I just wish the teacher's solution manual were available to anyone (specially if you are doing like me self study).

However I would recommend to anyone not exposed previously to probability, to get acquainted first with the subject by studying and solving all the problems from the excellent book of Probability (Modular Mathematics Series) by John McColl
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Most Helpful Customer Reviews on (beta) 3.6 out of 5 stars  30 reviews
20 of 21 people found the following review helpful
5.0 out of 5 stars A great intro text for Stochastic Processes 13 Mar 2011
By Matthew H. Holden - Published on
Format:Hardcover|Verified Purchase
I bought this book as a supplement to Resnick's "Adventures in stochastic processes." Basically I really liked how there is a lot of exercises with many solutions in the back of the book. It makes this text ideal for self study. It is not quite as rigorous as Resnick but it provides a lot of examples, intuitive explanations, and applications that make the book extremely valuable for any quantitative scientist. I would recommend this book as a main text for an upper level undergraduate class in stochastic processes, a text for mathematically minded scientists in biology, physics, and economics who want to learn some stochastic processes on their own, or as a supplemental text for a graduate class that focuses more on theory. In the latter case the book will provide added examples and explanations when you get lost in some of the mathematical formalism of more advanced books. Reading the simple non-rigorous explanation will allow you to go back to some of the difficult proofs with a better understanding for what you are trying to prove.
34 of 40 people found the following review helpful
1.0 out of 5 stars Horrendous 30 Mar 2011
By phsu - Published on
Format:Hardcover|Verified Purchase
Imagine a probability textbook with just equations and text. Seriously, with no diagrams whatsoever (except in some of the exercises). Imagine being "introduced" to Markov chains without seeing a single state diagram, joint probability densities without even an X-Y digram, probability spaces without Venn diagrams, conditional probabilities without tree diagrams. Not to go for the bubbly colorful textbooks, as I majored in physics and spent several years with black-and-white physics and math textbooks that show equations up the yin yang, but the saying "a picture is worth a thousand words" does not fail. If you use just this textbook, the best you'll be is an equation monkey with very little intuition. Also, certain tools that are extraordinarily useful and would make solving problems a heck of a lot simpler are left to be derived in the exercises -- so if you were never assigned that problem, you'd never see it, nevermind realize it's a very valuable tool. I've gotten an A in a college-level probability class before and am taking probability again only because my new graduate school requires we retake the course. I feel really sorry for whichever poor soul who's using this book as a genuine "introduction".
8 of 9 people found the following review helpful
5.0 out of 5 stars Thorough, readable, well-structured text with a good balance of theory and practice 24 July 2012
By Brooke the 3rd - Published on
This book is best for those with some exposure to probability and statistics. If you've had science courses that used probability but you've never actually taken a probability course, then this book could be perfect.
In my opinion, this text provides a strong foundation. It makes books like All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics), easier to use and harder to abuse.

- Clarity: There are no missing steps in the math, you don't have to doodle in the margins to derive the next equation.
- Mathematical ease: This is calculus-based probability but the calculus is not difficult and the algebra is crystal clear.
- Completeness: The book clearly presents core concepts concisely; it is not telegraphic. You will be introduced to probability distributions, conditional probability, Markov models, queuing theory, stochastic processing and methods for simulating distributions.
- Theory: The text mentions or proves relevant theorems at the rate of 1 every 10 pages. The proofs were simple and the theorems are crucial - for introductory texts, that counts as theory for me.
- Examples: There are many good examples that make it more memorable.
- Structure: Overall, I thought the structure was good. As a novice, I particularly liked the 2nd chapter on random variables - a clean approach to various probability distributions, their parameters and functions. As a scientist, I was grateful for the clear introduction to queues and stochastic processes.

Other reviewers have complained about structure and, since this doesn't really make sense, I am guessing that it comes from failed expectations. This is not a introduction to statistics. You won't find the Wald test, Bayesian testing, Pearson's chi-squared, a likelihood ratio test or any other workaday statistical test. If that is what you want, then go to "All of Statistics" (see above).

- Graphics (or lack thereof): I could have used more figures. Out of curiosity, I wrote a program to see probability density functions for different parameters and variables. Markov chains without actual transition diagrams seemed odd.
- Odd-man-out chapters: I didn't really understand the inclusion of the Reliability chapter (probably just me).
- Redundant/simple examples: For example, the Renewal chapter had near identical examples(in one, lightbulbs blown out, in another, batteries depleted) but nothing more compelling - what about evolution?? Mutation is a Poisson process, but sometimes the mutation creates a selective sweep which is a renewal process, so what kind of process is evolution? Horse kicks are Poisson but if you replace the horse every time it kicks someone, then that's renewal. So what's the likelihood of a horse kick with renewal? I would have enjoyed some more complicated examples.

Nitpicking aside, I thought this was a great book.
8 of 9 people found the following review helpful
5.0 out of 5 stars Best served with a strong background 23 Nov 2011
By MP - Published on
Format:Hardcover|Verified Purchase
This book is best served with a strong background in probability. I would recommend the same authors "A First Course in Probability" to acquire the knowledge necessary to really get the most out of this book.

As for this book itself, the first two chapters are pretty quick, cut, and dry. They cover the material necessary and adequately for later sections with no real B.S., but sometimes it can feel a little too dry (which is why I recommend a stronger background first).

Chapter 3 is perhaps the most important chapter in the book. I can not stress enough the importance of mastering the concepts in chapter 3 - conditioning is by far the most important problem solving technique in this book.

Tons of good exercises ranging from easy to very hard, and starred exercises have detailed solutions in the back.
6 of 7 people found the following review helpful
2.0 out of 5 stars Poor for learning, okay as reference 22 Oct 2011
By Y. Gu - Published on
While this book has it's merits, I found it to be unnecessarily convoluted in its explanations of basic models. Concepts such as stationary probability and communication, which can be explained by friends in 5 minutes are literally impossible to understand with the text due to the dense mathematical notation and the lack of pertinent examples.

The homework problems help with the understanding of the material, but the text itself does a poor job of conveying the information in a coherent manner (I guess you have to buy the solutions manual if you want to learn the material). The book complicates simple concepts and does not organize itself in a way that lends itself to self-learning. I had lecture notes from the professor, which clarified the material greatly. Beyond the 5-10 hours I struggled reading the book at the beginning of the semester, I only touched the book when I sold it to a friend.
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