Customer Reviews

Probability

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

 

 

I would guess all the intensely negative reviews are from "pure-math" types. But, if you need to understand how to apply probability to some real-world problem, this book is for you.

I have never encountered such an easy-to-read description of probability. Also, there are absolutely great, intuitive examples which are non-trivial and easily extended. I completely disagree that this book encourages memorization -- rather, there are many examples which give both an intuitive/thinking-about-it solution and a formulaic solution.

Also, there are easy-to-find "rules" for probablisitic-type functions and operations which are very clearly explained and accompanied with non-trivial examples.

The notation may be a little clunky, but it is very easy to find the definitions and the index is reasonably complete. Also, there are several valuable appendicies. Oh, and there are solutions to odd-numbered excercises and solutions to mock-exams. What's not to like?

I would recommend this book to those who need to know probability for their non-pure-math discipline (i.e. physics, engieering, life sciences, etc.) but can't afford to invest the time in a full course (although I'm sure a course which uses this book would be a great asset, as well).

This text presents the broad topic of probability in a clear-cut manner. The author provides as much theory as possible without the formal arguments needed for a graduate course. Instead, he uses logic developed throughout the course of the text to explain the theory in words. Also, his examples assist in completing the discussion on a topic. As both an undergraduate and statistics tutor at UC Berkeley, I believe that this text is superior to others when it comes to explaining probability to a beginner.

I used this textbook in an undergraduate class, and went back to it to study for SOA/CAS Exam 1/P. The examples and explanations were run of the mill, but the problems... wow.

There was a wide range of problems, in scope and in level of difficulty. They ranged from medium to hard to impossible. Some of the more memorable ones were research-level problems that required you to do a little bit of independent research on the internet, and the hardest problems could easily take you all day to solve. The problems were easily the strongest part of the book and you will learn the necessary concepts by solving them - the examples and explanations are really just there as a guide. I can attest to this because I did them ALL, 709 of them in total - a feat that took me roughly two months and enabled me to pass Exam 1/P with flying colors.

Overall, I found the explanations and examples to be less than top-notch, but the problems will really test you. Just make sure to work in groups and ask for help, and stick to problems that are relevant to the course (or exam) - otherwise the book can chew you up and spit you out.

P.S. This text does not have a section on moment-generating functions, so you'll have to find another source for that topic. Wikipedia has a good article on the subject.

More than most introductory texts this one is self contained without being overly pedantic. I took Prof. Pitman's course with a preprint of this book and then bought the published version as a reference. There really are no better introductory texts (I've purchased many) for working with the material at this level. Accompany it with a good problems book (such as Gunnary Blom's "Snapshots") and follow it with Allan Gut's "Intermediate Course in Probability" and you're all set.

Professor Pitman's text was my introduction to probability, and an excellent one at that. The prose is clear and classic probability problems are used as examples and homework problems. The diagrams are modern and instructional, and the book is very well edited. I recommend this book to those interested in learning the basics of probability. P(Finding a better intro text)= 0.

After reading about 15 books involving elementary probability theory, including those written by Hoel, Port, and Stone (which my prof. unfortunately used for my class) and also Sheldon Ross, I came to the conclusion that Jim Pitman's Probability book is the best informative and intuitive book. It does not clutter the pages with needless notation that gets beginning students confused and more often than not intimidated. Being a student at UCBerkeley, I would like to praise Prof. Pitman on creating and excellent book.

Professor Pitman's text was my introduction to probability, and an excellent one at that. The prose is clear classic probability problems are used as examples and homework problems. The diagrams are modern and instructional, and the book is very well proofed. I recommend this book to those interested in learning the basics of probability. P(Finding a better intro text)= 0.

A useful and relatively thorough text for non-mathematics majors (who would require a bit more rigor). The organization of the text is not perfect (for example, Bayes' Rule just sort of sits in an introductory section) and keeps the book from five stars, but otherwise it's a fine introduction, particularly in light of some of the more inscrutable texts on the market.

The explanations are dense, worked problems don't reflect concepts taught in book. It is completely unhelpful as an instruction material.

A horrible book. The text is convoluted and never clear, the exercise problems are completely outside the subject matter of the chapters, the chapters themselves are hardly explanatory (you get two-four paragraphs of "whats" and maybe three examples total, and folks these chapters are meant to cover a lot of ground), and there is hardly any explanation as to WHY this stuff works. A pointless book that can only be used in conjunction to a very well taught class. This book will NEVER teach you anything by itself. I cannot see anyone who learns through this book being able to perform this math after a couple of years, it is a clear book for monkey-see-monkey-does-monkey-has-no-clue-what-went-on-but-got-the-right-answer math.