Very well written book. Excellent explanation of basic concepts, and I echo the positive reviews of other readers.

This book is pretty good on theory, but doesn't have enough practical examples to be a standalone text.

This book is generally excellent, with clear explanations and a good balance of rigor and practical application. You won't find proofs of everything, but you will find excellent guidance and intuition through the various topics, especially the fundamentals. The only significant complaint I have is that certain topics are covered too briefly (such as the central limit theorem or stochastic processes) or not at all (e.g. null hypothesis significance testing).

Much of this will be rememedied in a second edition, which will include a welcome added chapter on estimation. We used a preliminary version of the chapter in the probability class for which the book was written, and it's fantastic. It was the most interesting part of the book, and I'm sorry that I didn't wait to buy the book when I could have gotten the final version.

I hope the second edition also fleshes out the chapter on Markov chains, which are presented very tersely, and without the use of linear algebra. Studying Markov chains without using linear algebra is like studying differential equations without the Lapace transform; you can do it but it's much harder than it has to be.

In the end, the terse coverage of certain topics is more than made up for by the fine handling of the basics, and I unreservedly recommend the book for anybody studying the topic for the first time.

This is a must buy for people who would like to learn elementary probability. The only background you need is basic series and calculus. This is the best probability book I have seen.

The shipping was very fast and the book was just as described. I would recommend this seller without hesitation!

Bertsekas has truly been a savior in helping me integrate the concepts of probability. I tried most of the standard intro books before finally settling in with this comforting and rewarding book. The list included: Pittman, Ross, and Hoel. None of these books were effective in solidifying the concepts in my opinion. I think Bertsekas is also an excellent choice for brushing up for an actuary exam or self-study.

First all, everyone wishing to learn probability comes from different background, math level, and motivation. There is no book that suits all. Recently I needed to know something about moment generating functions. With all my advanced engineering background though, I find it difficult to get into probability.

So I bought the following supposedly introductory texts: Ross, DeGroot, Stirzaker, Bersekas & Tsitsiklis. To me, Ross seems like a review lesson to cram for finals; it's choke full of examples but fairly spare in exposition. DeGroot is the opposite, long on descriptions but short on examples; by the time it finishes describing the problem, you have forgotten how to solve it. Probability is set up more as a prelude to statistics in the second half of the book. Stirzaker calls his book "elementary" the way Sherlock Holmes dismissed a case after slogging all night through the English bogs. It is more for the well-drilled boys from elite British "public" (private actually) schools. Bersekas comes closest to what I look for in a text, straightforward in prose with a judicious selection of examples to explain theory.

For beginners, the best approach I found, in the end, was to go the local community college and buy the text used for Finite Math. Usually, there are 3 to 4 chapters that introduce probability.

Such a text is aimed an audience from wider academic and language backgrounds, as community colleges are mandated to do. Therefore, probability is taught in simple, plain-spoken language crafted through multiple editions. One such is Finite Math, by Karl J. Smith; however, many others like it will do. For self-study, one might start in the chapter on probability to understand the author's approach, then go back a chapter or two to pick up the permutation and combinatorial math needed to calculate probability. Another alternative is just to enroll in a Finite Math course at a community college. Generally, such a course stops at Markov's chain which is enough to get you jump started in probability.

In any case, a good Finite Math text gives plenty of examples with clear, succinct, and layman-like explanation to help you tackle Ross' book or supplement any other at a higher level. If you plan to apply probability to your work, then shop around for another text after you get the basics. The thicker tomes delve more into theory which is good because real life problems are seldom like the examples given. However you can't go wrong by planting your feet solidly on a good Finite Math text first.

First all, everyone wishing to learn probability comes from different background, math level, and motivation. There is no book that suits all. Recently I needed to know something about moment generating functions. With all my advanced engineering background though, I find it difficult to get into probability.

So I bought the following supposedly introductory texts: Ross, DeGroot, Stirzaker, Bersekas & Tsitsiklis. To me, Ross seems like a review lesson to cram for finals; it's choke full of examples but fairly spare in exposition. DeGroot is the opposite, long on descriptions but short on examples; by the time it finishes describing the problem, you have forgotten how to solve it. Probability is set up more as a prelude to statistics in the second half of the book. Stirzaker calls his book "elementary" the way Sherlock Holmes dismissed a case after slogging all night through the English bogs. It is more for the well-drilled boys from elite British "public" (private actually) schools. Bersekas comes closest to what I look for in a text, straightforward in prose with a judicious selection of examples to explain theory.

For beginners, the best approach I found, in the end, was to go the local community college and buy the text used for Finite Math. Usually, there are 3 to 4 chapters that introduce probability.

Such a text is aimed an audience from wider academic and language backgrounds, as community colleges are mandated to do. Therefore, probability is taught in simple, plain-spoken language crafted through multiple editions. One such is Finite Math, by Karl J. Smith; however, many others like it will do. For self-study, one might start in the chapter on probability to understand the author's approach, then go back a chapter or two to pick up the permutation and combinatorial math needed to calculate probability. Another alternative is just to enroll in a Finite Math course at a community college. Generally, such a course stops at Markov's chain which is enough to get you jump started in probability.

In any case, a good Finite Math text gives plenty of examples with clear, succinct, and layman-like explanation to help you tackle Ross' book or supplement any other at a higher level. If you plan to apply probability to your work, then shop around for another text after you get the basics. The thicker tomes delve more into theory which is good because real life problems are seldom like the examples given. However you can't go wrong by planting your feet solidly on a good Finite Math text first.

I found this book a very readable, concise and useful introduction to probability.
Designed with application in mind, it emphasizes intuitive understanding and doesn't contain any boring formalism.
The only regret that I have is that avoidance of matrix calculus leads to lack of some
results, notably in markov chains (anyway this subject is well covered).
I strongly recommend this book to anyone looking for a fundamental text on applied probability.

I am a university student taking a probability course and found this book to be invaluable.

The book actually assigned to our class was Sheldon Ross' A First Course in Probability. I found Ross' book unreadable so I began looking for another text in order to help myself pass the class.

After reading numerous reviews I decided on an Introduction to Probability. The book is well written and easy to understand. The main points are highlighted and made extremely obvious. In addition they are backed by step by step easy to understand examples. Another feature I found very helpful was the use of graphical examples to reinforce the points being made.

In short I would recommend this book highly to anyone looking for an introduction to probability.

Update: I finished my probability course in May with an A. I completely stopped using Ross' book around the time of this review. This book was by far the most useful tool I had. I strongly back my original recommendation. I will be graduating this fall, and this book has turned out to be one of the best mathematic books I have encountered thus far.

I say this for the following reasons. First, the layout of the book, and the order it presented material is very intuitive and helpful. Second is how well the book reads. My experience with quite a few mathematics books has been the following. The math books are written by mathematicians. While being a mathematician may qualify you to teach a subject, it does not generally translate into an ability to put your ideas into written form. The result is a book that is not read by the students, but instead only consulted when all other methods of information retrieval fail. Introduction to Probability does not share this fate. The writing style of the book is very straight forward and easy to understand. While this may sound redundant, I personally think this is one of the best reasons to buy this book.

I am a university student taking a probability course and found this book to be invaluable.

The book actually assigned to our class was Sheldon Ross' A First Course in Probability. I found Ross' book unreadable so I began looking for another text in order to help myself pass the class.

After reading numerous reviews I decided on an Introduction to Probability. The book is well written and easy to understand. The main points are highlited and made extremely obvious. In addition they are backed by step by step easy to understand examples. Another feature I found very helpful was the use of graphical examples to reinforce the points being made.

In short I would recommend this book highly to anyone looking for a introduction to probability.

This is an excellent introductory guide to anyone interested in probability. The book is written with a general audience, but there are some examples that are specific to information and communication theory. I'm especially fond of the challenging problems at the end of the book. The language is lucid, and the concepts are explained in a very clear and logical fashion.

I remember referring this book for my Undergraduate class in probability and it explained difficult concepts in the most simplest way by using good visuals (diagrams, graphs etc). Therefore, it's a very good book for anyone starting out new since probability concepts can be hard to grasp initially. Highly recommend for students interested in stochastic processes and probability.

This is really an excellent introduction to probability. The author does a good job of maintaining just the right balance between math and intuition. For someone just starting out, this book is a good choice. It will lay a firm foundation for later, more rigorous studies.

One negative comment: This volume appears to have been published by the author's own (tiny) publishing company. The book's quality would have been improved if the author/publisher had engaged the services of a proof reader and editor. Some of the word usage is just wrong, and commas are scattered about more or less randomly in the text. While this doesn't detract from the quality of the information, it's a distraction.