Customer Reviews

Elementary Probability for Applications

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I'm currently enrolled in an introduction to probability class at my university and, unfortunately, I'm forced to use this book. This is definitely one of the most frustrating textbooks I've ever had to use in my entire academic career. Many topics aren't explained well and the "example problems" skip countless steps -- it's like you already have to be familiar with the material to understand what's going on. Seriously, you'd be better off learning from Wikipedia. If this isn't bad enough, the book is absolutely full of errors, including the answer key at the back of the book that provides solutions to odd problems.

Nothing like spending 30 minutes confused, frustrated, and stressed because I'm being told I have the wrong answer when I have the correct one. This book blows, don't buy it unless you have to.

I found the book to be just fine. While it does have several typos and a few incorrect answers in the back of the book, it is not a bad text book. Probability is a subject that allows its users to "think out side the box". Its not meant to be a read once and never think again subject. In that regard, this book does a good job. I found that at times this book felt cumbersome. When I thought about the topics and on occasion referenced previous pages, it flowed smoothly. The purpose of this textbook is to teach by example, if that is not a learning style that you thrive in, consider buying "Mathematical Statistics and Data Analysis" by John Rice as it focuses on a more traditional learning style.

I taught a course using this textbook called "Intro to Probability" for mathematicians, statisticians and scientists. There were about 120 students enrolled in 2 sections, all with calculus background including series. It went very well. The book gets to the point quickly. For instance, random variables are right in the first few sections, unlike some books that first treat combinatorics at length. The examples are excellent. For instance, in addition to covering the Monty Hall problem, Durrett then reviews a recent news item of a social scientist who used this to explain a phenomenon which was previously believed to be a case of cognitive dissonance in primates. I also like that in the final chapter Durrett treats some elementary topics in statistics, such as the 95% confidence interval, because that is not emphasized enough in standard probability textbooks. The only minor drawback I see is that in the section on the Central Limit Theorem, there is not much in the way of a proof. Of course in the standard textbooks the "proofs" are not really proofs anyway. He does give the proof of the Weak Law of Large Numbers and states the Strong Law of Large Numbers. In our class, we spent the last 2 weeks going over a proof of 2 special cases of the CLT for the p=1/2 binomial distributions and for sums of exponentials (i.e., Gamma distributions) which leads to Stirling's formula. I also used Durrett's excellent coverages of additivity of expectation and Chebyshev's inequality to briefly explain the Borel-Cantelli lemma (1) and motivate the proof of the SLLN. The exercises in this book are great. It is true that 1 or 2 have typos in the back of the book. But we coded alternative problems based on his into WeBWorK, a computerized online HW program, anyway. With a small amount of effort the instructor can catch all the typos and even use them to raise the discussion of things like checking answers against intuition, etc. As one previous reviewer said, with a good instructor at hand, the few typos are not a problem at all.

There are tons of typos in this book. This is my probability textbook. If you have a good professor in probability in this course, this would be a good textbook. If you want to study your self, you had better change another book. It's impossible to you to study your self.Like in markov chain chapter, how many concepts in that? Our professor give us some extra notes to understand them. Also the text book just tell you that you should use it,like fundamental matrix, it does not show you the reason. It's pretty tough.

This books content is decent, however a lot of the proofs contain typos, making them hard to read and understand.