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.

A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions.

A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states.

Simplified Approach for Analyzing Nonhomogeneous Poisson processes

Additional results on queues relating to the
(a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system,;
(b) inspection paradox for M/M/1 queues
(c) M/G/1 queue with server breakdown


Many new examples and exercises.

Customer Rating:
Summary: Very usefull and easy
Comment: I am not a statistician and yet I loved the book. The exercises are hard, but very helpfull (maybe it should have more answers). There are a lot of examples in each chapter, making easier to understand the theory.

The author look to explain the intuition behind some theorems and proofs, which is excellent. I have almost no hard background in statistic and math (just knew how to derive and integrate and some notions of calculus of probaility) and I was capable of understand almost everything I studied (from chapter 4 to 8).

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Customer Rating:
Summary: New To This Edition Are Five New Sections
Comment: ".....NEW TO THIS EDITION ARE FIVE NEW SECTIONS, and numerous new examples and exercises, many of which focus on strategies applicable in risk industries such as insurance or acturial work....."

"Other Academic Press books by Sheldon Ross:
Simulation 3/e, ISBN 0 12 598053 1.
Probability Models for Computer Science, ISBN 0 12 598051 5.
Introduction to Probability and Statistics for Engineers and Scientists 2/e, ISBN 0 12 598472 3."
[from the book of the back cover]

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Customer Rating:
Summary: does not explain the concepts so well; just one proposition after the other
Comment: We had this book for a 4th year Computer Science - Statistics course.

I agree with some of the other reviewers that - inspite of claiming to be an 'introductory' text book - it does not explain the concepts so well.

e.g. Bayes Theorem has been introduced in like half a page with absolutely no explaination of prior and posterior probablities and the underlying concepts (something I learnt when we applied Bayes Formula in a Neural Networks & Data Mining course)

So all you get are the formulae from this book (at least in the first few chapters that I read), where the author should have spent more time 'introducing' concepts.

The solved examples are ok, but very academic - and there is no way to be sure of your answers for the other non-solved questions (unless you have a lecturer to discuss them with)

2 Stars - because they ought to start writing math books that regular people can read and understand and appreciate - not just math prodigies

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Customer Rating:
Summary: Dense and difficult to follow.
Comment: This book contains a wealth of information about probability models, but it's so hard to follow that I can't extract any of that information to make any use of it. From the other reviews, I gather that it is a good resource for some. But this definitely not an INTRODUCTION to Probability Models unless you have a very strong background in general probability.

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Customer Rating:
Summary: one of the best introduction to probability and stochastic processes
Comment: Understanding probability requires various resources to read. I think this book is one of the irreplaceable element in these resources. It is an introduction book as the name implies. Examples are illuminating the subject very well.

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