Elementary Probability for Applications [Hardcover]

Rick Durrett (Author)

Book Description

ISBN-10: 0521867568 | ISBN-13: 978-0521867566 | Publication Date: July 31, 2009 | Edition: 1

This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples. The examples contain all the old standards such as the birthday problem and Monty Hall, but also include a number of applications not found in other books, from areas as broad ranging as genetics, sports, finance, and inventory management.

Editorial Reviews

Review

"The book has a nice interplay between probability modeling and scientific applications, whether from biology, sports, or discussions of China's one-child policy. Many of the examples are thought provoking, including ones on DNA samples for paternity cases and others about the O.J. Simpson trial. As an instructor, I enjoy digging into these examples in class. And the large selection of interesting problems builds basic skills and deepens or extends the main ideas."
Professor Michael Phelan, University of California at Irvine

"While the topics covered are standard for any number of books, Durrett adds diversity, innovation, and plenty of exercises that are sure to captivate the reader and excite the student. Students and instructors alike will find the text both useful and very entertaining."
James Van Speybroeck, Computing Reviews

"Highly recommended."
W. Van Arsdale, CHOICE

Book Description

This clear, lively introduction to probability concentrates on the results that are the most useful for applications. It is designed for a one-semester course for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples.

See all Editorial Reviews

Product Details

• Hardcover: 254 pages
• Publisher: Cambridge University Press; 1 edition (July 31, 2009)
• Language: English
• ISBN-10: 0521867568
• ISBN-13: 978-0521867566
• Product Dimensions: 9.8 x 7.5 x 0.8 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 3.4 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #49,965 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

6 of 8 people found the following review helpful:

2.0 out of 5 stars Terrible textbook, filled with errata, March 15, 2010

By 

JD - See all my reviews

This review is from: Elementary Probability for Applications (Hardcover)

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.

4.0 out of 5 stars A Good Start, November 23, 2011

By 

Poisson825 "sigma^2" (CA) - See all my reviews

Amazon Verified Purchase

This review is from: Elementary Probability for Applications (Hardcover)

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.

5.0 out of 5 stars A thin alternative to the standard textbooks, January 3, 2011

By 

S. L. Starr (New York, USA) - See all my reviews
(REAL NAME)   

This review is from: Elementary Probability for Applications (Hardcover)

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.