Customer Reviews

First Course in Probability, A (7th Edition)

5 star:		(8)
4 star:		(6)
3 star:		(3)
2 star:		(3)
1 star:		(5)

 

 

The title of this book is a bit of a misnomer. A more apt title would have been "First Graduate Course in Probability" or "A Second Course in Probability". The book description describes this as an introduction for students with an understanding of only elementary calculus. However, I believe that very few people with a background in only elemetary Calculus are going to be able to follow this text which presupposes facility with proof techniques like mathematical induction and a moderate level of mathematical maturity. Ross does not do any hand holding. Proofs are short and to the point, explanations are terse and compact, "obvious" steps are skipped and left to the reader to fill in. So if you are not prepared to follow terse mathematical explanations that are short on cursory explanation, then this may not be the book for you.

For math majors and other students with a strong mathematics background, however, this may serve as a useful reference. It is concise, elegant and chock full of example problems with solutions. But it all depends on what you are ready for. Some may find the excessive number of example problems distasteful and prefer a less cluttered treatment. Others may find that, despite the examples, the book is not "applied" enough. In my opinion, this book is not suitable as a first course in probability for anyone but mathematics majors. You will get the most out of this book if you are already familiar with the subject, or if you have a talented teacher to fill in the numerous gaps. For actuarial students and engineers, you may want to look for a more expository volume like "Introduction to Probability" by Bertsekas.

Contrary to its title, this book has helped me through several probability courses. I used this book not only to study for the first actuary exam, but also as a supplement for my intermediate and doctoral-level probability/inference courses. Ross fills in gaps left by texts such as Rice, Cassella and Berger, etc., by spelling out properties of various distributions, and showing how they relate to eachother, and by doing many many examples.

Incidentally, save yourself the money and get an earlier edition. I have the fifth edition, which was not even the current edition at the time that I bought it, and it's perfect as is.

This was a textbook for a probability course that I took, and I did not find it very useful at all. The book is incredibly thick and large, but there is relatively little information in it. The extra bulk is not due to explanatory prose, discussion, or optional topics, but rather, an abundance of examples, some of which are good, but some of which are inappropriate and/or poorly carried out. In particular, I find that the order in which the examples are presented is not optimal, and the amount of examples on a given topic is not optimal either. There also needs to be much more discussion, instead of just going over specific problems.

Overall, the book is unreadable, even though it's at an elementary level.

The only redeeming quality of this book is that its exercises are fairly challenging, interesting, and there is a "self-test" section at the end of each chapter which provides fairly good explanations of how to carry out the problems.

My last criticism of this book is that it's clear that the publisher is trying to milk this for as much money as its worth--by the 7th edition, the book should be very refined, and honestly, looking at previous editions I see absolutely no improvement. I honestly question any book that goes beyond 3 or 4 editions...I think it's a money-making scam and you shouldn't waste your time with it when there are so many good texts on probability out there.

I've only read the first four chapters of this book so far, but overall, I am enjoying the book. In order to give a sense of how difficult the book is (or perhaps how slow I am in picking up the material) - it sometimes takes me a full hour just to read 3 pages. Furthermore, sometimes, I have had to put the book down and reread the pages another day to be able to comprehend the material. This is with a goal of really trying to understand each page. My math background includes classes in Calculus, Linear Algebra, and Introductory Differential Equations. Each chapter has three sets of problems: chapter problems, theoretical problems, and self-test problems. The self-test problems have concise solutions that also can take a some time to understand. There are also a few typos here and there - not that many though. I would recommend this book only to those who are highly disciplined and persistent with studying math. I would also recommend finding a person knowledged in Probability for questions you'll definitely have. For me, I've had to also do a lot of the problems to really understand the material. Lastly, this book has been my first introduction to probability.

Maybe I'm too used to the theorem-proof structure of other mathematics textbooks. This one leaves me cold: too little is made of the exposition, while the author leans too much on the copious amounts of examples as a crutch. The examples, alas, aren't terribly good; the author pulls ideas from god only knows where, without explanation, often stopping me short in the middle of reading the answer to what should be a simple problem.

I don't recommend this textbook. Sadly, I don't know of any better ones. The textbook recommended for the first actuarial exam - _Probability: The Science of Uncertainty_ - is a better book overall, but lacks the requisite depth for a really thorough treatment of the subject.

I used this book 18 years ago in an "introductory" probability course for advanced undergraduate/beginning graduate applied mathematics students. The course didn't assume any previous knowledge of probability, but it did require a background in multivariate calculus, and for this type of course this text is appropriate. Despite the plethora of examples that it provides, this would be a terrible introductory text for freshmen or sophomores, especially those who (intend to) major in the social sciences, as it really is focused on developing the theory behind the subject.

As I recall, the first 2 chapters treated combinatorics, in a frustratingly intuitive fashion, in the sense that it seemed the only way to do the problems was to try to copy examples given in the text. There were also some confusing paradox-type problems, where it seems as if more than one answer is possible depending on one's perspective, and for these the text did not provide much guidance.

Once beyond these early chapters, the book became much more analytic, essentially becoming an exercise in multiple integration, which I, as a math major, found to be much easier, but many other readers (such as other reviewers here) would probably feel the opposite. Still, I recall spending a disproportionate amount of time that semester on this course, essentially because of the difficulty of the text, and in particular, I recall many tedious problems that revolved around summing infinite series, which can be daunting until one develops the necessary bag of tricks. Still, I think the book did do a good job of explaining the theory of probability, even if this was not much use in solving exercises.

While I have rated this as 4 stars, I can understand how those who don't share my enthusiasm for challenging texts would rate it lower.

Well first off I would like to tell anyone who doesn't have a solid working knowledge of calculus (including multivariate) to avoid this book as it requires multiple integrals and infinite series and sequences. Now onto the good and the bad:

THE GOOD:

This text explains concepts very well and is FULL of examples. I mean literally 3/4 of the book, maybe more, is examples. Every chapter also has a section of problems that have partial solutions, which can come in very handy. This is pretty much all that is good about this text, but keep in mind that explaination is the most important part of any textbook.

THE BAD:

The proofs skip plenty of steps. And I mean plenty, so much that a proof in the book would take 5 lines but when my professor proved it in class it would take him nearly 15. Also while there are tonnes of examples, too many are theoretical and very hard. I took this course first term of my second year, and it's too much to ask from second year students to solve these kinds of questions. Also there are lots of homework questions, however no solution manual, only the very few solved in the back of the book (which is better than nothing I suppose). The book also costs a hefty amount of change and is suprisingly small, not even an inch thick. However the worst thing about this book is how the author leaves important things in with the text often. Often key terms and formulae lie within the text, and are made to not look important at all (so go to class to see what's stressed!). However most these things are small, and overall the text is a good intro to probability theory.

I don't understand why so many reviewers are claiming you need a "strong" math background. You do need a math background, this *is* mathematics, right? You need to know your calculus, of course. Why would you hope or think otherwise?

But Ross won't BS you into pushing sigma-algebras at your face, cluttering up the reading with "rigour", when you can't make sense of rigour, since you haven't taken measure theory (we all haven't, at this point, and most will not). So Ross is not making any false claims. Let's keep it real.

The book is loaded with examples, as many reviewers mentioned. The examples are relevant, with many a classic problem present. Some examples may be hard, but yet again Ross is not fooling you with problems so stupid they're not even worth solving. Besides, there are loads of exercises, not all easy, not all hard. You only learn through examples and through exercises. I've seen problems on my exams that are like the ones Ross exemplified. Expect the same, even if you are following a "nice" easy-reading book with *no* examples. I hope you get my drift.

Maybe Ross could be made better with more verbose explanations? Possibly. Yet, I found out this is one book that I can't do without. I don't think the same about a bunch of other introductory texts I have. I could toss away a dozen, but I would keep Ross. If you feel this is too hard, you can probably benefit from another text to use side-by-side, like Dekking's.

Anyways, this is an excellent book. Work it! Don't believe all the whining (maybe their teachers chose the wrong book for the wrong crowd). You do *not* need to be a math genius to read this book. Math, physics, engineering, finance undergrads will feel at home with Ross.

Every student like examples, but Ross over-uses them, to the point of insanity. He introduces most of the material in the course of working specific problems (c.f. in the abstract). I, for one, think this is an extremely poor way to present mathematical material; after reading an example, you will have to distill the salient techniques and concepts from it. This can be quite difficult, since his examples are often quite involved, yet not worked with clarity and thoroughness. Thus, it's sometimes hard to see where the example ends and the theory starts; put another way, you'll understand what the author is doing without understanding *why* he's doing it.

Overall, I would avoid this text.

This was the textbook for my upper-division, undergraduate course in probability theory. At my university, there are three courses that each serve to teach basic probability theory. The most basic course, which is lower-division and primarily intended for those majoring in the social science, does not use this book (or calculus, for that matter). There is a course in probability intended for those majoring in the physical sciences, engineering, or the computational sciences (for whom an upper-division course in probability is required), and they don't use this book either.

Then there is the course in probability for math majors (the course is required), of whom we have three varieties: the pure, the applied, and the actuarial. That is the course and the audience that makes use of this book, and in that context it works very well. By the time that any of us reached this course, we've had the lower-level calculus sequence, matrix algebra, discrete math, differential equations, a very proof intensive set theory course. The professor covered the material in the standard fashion of upper division theoretical math courses, the tried and true proof-theorem-example approach, and the book worked well for us.

For those that have less experience or fluidity with either mathematics or proof techniques may have a different experience, and I can't presume to speak for them. Hence, caveat emptor.