- Hardcover: 720 pages
- Publisher: W. W. Norton & Company; 4th edition (February 13, 2007)
- Language: English
- ISBN-10: 0393929728
- ISBN-13: 978-0393929720
- Product Dimensions: 7.4 x 1.7 x 10.3 inches
- Shipping Weight: 3 pounds (View shipping rates and policies)
- Average Customer Review: 4.0 out of 5 stars See all reviews (88 customer reviews)
- Amazon Best Sellers Rank: #143,525 in Books (See Top 100 in Books)
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About the Author
David Freedman received his B.Sc. from McGill and his Ph.D. from Princeton. He has worked as a consultant for the City of San Francisco, the County of Los Angeles, the U.S. Department of Energy, and the U.S. Department of Justice. He has written several previous books and numerous technical papers. He is a member of the American Academy of Arts and Sciences and teaches at the University of California, Berkeley.
Robert Pisani received his B.A. and Ph.D. at the University of California, Berkeley. His research interests include probability models of market-price behavior and the statistical valuation of financial instruments.
Roger Purves received his B.A. at the University of British Columbia and his Ph.D. at the University of California, Berkeley, where he currently teaches. His research interests are in the mathematical foundations of probability theory.
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Top Customer Reviews
This is one of the top half-dozen texts of my entire college career.
Not only do the authors make statistics accessible and even fun, they do so in a consistently smart style that simultaneously simplifies statistical concepts while not pandering in the quality of language overall, or occasions for clever asides. While many professors will end up using modern calculators for the problems, the text bases its lessons on the use of tables (normal, t, and chi-square). I found myself following both the professor and, electively, the text for a more full understanding of "old school" methods. Each chapter has enough embedded problems (with answers at the end of the text) that the reviews and other materials provided by my professor were often redundant. I wish I had access to the answers for each chapter review questions, but that can hardly be a criticism in my "student" copy of the text.
I'll be revisiting this book long after I've ceased being a student. It has helped me have more informed attitudes about statistical products in general, which I suppose was a point of the course and the text.
I do have one complaint. I like math and at a few points I wanted to tell the authors to quit teasing me and just give me the equation already. For example, they take several sections of text to introduce correlation and linear regression before finally introducing the actual linear equation. Maybe it's better to introduce it that way, I'm not a teacher. Others have mentioned the lack of standard nomenclature in this book but I can't see how that would be more than a minor inconvenience moving to a more advanced text. Another reviewer mentioned Statistics Unplugged by Sally Caldwell. I also have that book and though it has more standard nomenclature, I found it to be "wordy" and not as intuitive as the book in this review.
What I found in a lot of statistics books are formulas. There was no intuition or motivation as to how those formulas were arrived at. Some books state the assumptions and then give you the formula, which means you become just a little better than the person who knows only the formula, because you also end up memorizing the assumptions. Then there are 1 or 2 solved examples for you to look at and apply the same approach on 10 more exercises. You just need to figure out which number is the symbol (say, the Greek letter mu) in the formula and plug it in. These books make a wonderful choice for students preparing for exams and getting good grades by rote learning, but I know through personal experience, that such learning can take someone only so far.
Other books (like Naked Statistics or How To Lie with Statistics) are entertaining and useful, but you do not learn much about actual problem solving.
Then I started searching more for good introductory statistics books and some people on the Reddit forum on the best introductory statistics book had recommended this book. I decided to give it a try, especially since the 4th edition is the latest, and the used copies of the 3rd edition are now available for $10 or less.
From the preface of this book, one can see what the authors have offered in this book:
"Why does the book include so many exercises that cannot be solved by plugging into a formula? Few real-life statistical problems can be solved that way. Blindly plugging into statistical formulas has caused a lot of confusion. The book takes a different approach: thinking."
Just reading chapters 1 and 2 (the first 30 pages) on controlled experiments and observational studies, one can realize the wealth of insight this book has to offer. Or just read section 1 in chapter 1 on the Salk vaccine field trial and you would be amazed at how even a US national foundation could commit an inadvertent mistake in its statistical study.
This book is probably not for students only looking to get good grades in classes or competitive exams. (You can see plenty of 1 and 2-star reviews for this book by such people.) It is for people who really want to learn and understand statistics and apply it practically in their jobs and real life to solve actual problems.
The only reason for giving 4 stars for this books is that the fourth edition is priced exorbitantly high!