Like other books in their math series, it is an excellent workbook or refresher course, but cannot be used as a primary textbook. Good for:
**supplementary exercises if you are currently taking a probability course
**you just finished a course, but need more practice
**you took a course, oh so many years ago, but need to brush up
**you have a real calculation you have to do (e.g. you have polling data, and want know if marital status and voting in a presidential election are independent)

It has these chapters:
**set theory (venn diagrams)
**techniques of counting (notation, diagrams, binomials)
**introduction to probability (sample spaces, axioms)
**conditional probability and independence
**random variables (making calculations)
**binomial and normal distributions
**markov processes (markov chains and matrix calculations)
**descriptive statistics (mean, variance, standard deviation)
**chi-square distribution (calculating goodness of fit)

This happy workbook has lots of worked out examples to show you how it is done, and lots of supplementary problems with answers so you can practice on your own. Since the chapters are only weakly dependent on each other, you can skip around and do not have to go through them in order.

I highly recommend this book. The power is in the worked problems. In class we are using Sheldon Ross's book but I think it was too hard to read. This book simplified a good amount of the material and boosted my confidence in the class. Again highly recommended.

I found this book a simple, concise, and fairly easy introduction to probability theory. Most of the text doesn't require knowledge of calculus or linear algebra, but the text can serve to motivate studying of calculus and linear algebra as it does have some parts and problems which need calculus. The inclusion of a separate chapter, for review or to learn some basics, on set theory also makes this text as it helps to show how set theory gets applied. The classical birthday problem comes as an interesting way to show how probability theory can help us compute probabilities we can't directly count, and how probability can lead to ideas that expand our thinking. The last chapter on Markov chains helps motivate knowledge of linear algebra and also might help one analyze board games such as Chutes and Ladders. The authors graph-theoretic diagrams can also help to motivate knwoledge of, and the relevance of graph theory, and how it has relations to linear and vector algebra.
The difficulty of the solved problems varies from "plug-and-chug" problems to proofs that require a decent dose of thinking, "untangling" of definitions, and drawing out of consequences. In my opinion, this makes the book neither too easy, nor too hard, and thus helps to facilitate enjoyment of the problems and insight. Since there exist many solved problems, one can fairly easily figure out where those errors occur. Even if you know lots of calculus I would still recommend this over Spiegel's Schaum for learning probability theory, as this book includes its chapter on Markov chains.

This is a good book to have in your self for quick reference. I have many books from Schaum's Series and always found them handy at times. I am in the filed of science for so long that I have stopped counting years. Students and teachers all should have books such as these; students can learn a lot from the examples and apply the procedures discussed therein to different problems.


A note of warning -- do not expect tofind everything you are looking for in these books. However, it is safe bet that you will always find interesting problems that are solved in these books.