- 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: 100 customer reviews
- Amazon Best Sellers Rank: #59,600 in Books (See Top 100 in Books)
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Statistics, 4th Edition 4th Edition
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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.
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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.
First, to address the flaws. Many critical reviewers seem to bemoan the lack of formulas and mathematical notation in this book, but I haven’t found this to be a problem at all. If you want this to be a part of your course, simply type up a formula sheet with the formulas in both English and mathematical symbolism, and — voila! — problem solved. As long as I also do problems on the board and on the test and quiz keys using both English and symbols, my students have not found this to be an issue at all.
A much more serious problem is the non-standard usage of the term “standard error.” In most textbooks, SDs (standard deviations) are for formulas using the parameter σ (or p), and SEs (standard errors) are for formulas using the statistic s (or ˆp ). This is the dominant convention.
However, in the Freedman book, SDs are for lists of numbers, and SEs are for random variables. (He even has an illustration underlining this point on p. 291). Although I do see pedagogical value in this non-standard convention (it makes the students mindful of whether they’re dealing with a list of numbers, or with a chance process) I have to agree with the critics that this could be very confusing to students who go on to more advanced courses. I deal with this issue by making it clear to the students that this usage is non-standard.
The reason that I love this book — in spite of it’s flaws — is two-fold. First the quality of the problem-sets is at a deeper level than is typical in most introductory statistics books. Secondly, I love the wonderful use of box-models to derive all of the statistical techniques. It’s akin to teaching students how to solve quadratic equations by completing the square; when they finally do learn the quadratic formula, they understand immediately where the formula came from. It’s just a formalization of what they’ve already been doing.
In so many statistics books, it’s just one big mess of magical formulas that the students need to learn to use, but why they work and where they come from remains a mystery. Moses might have brought them down from the top of Mt. Sinai, for all they know. (Yes, yes, I know that you can derive them on the board in class, but — let’s face it — it will mostly go in one ear and out the other.) The Freedman book promotes understanding at a deeper level. Indeed, by using box models, a talented student can derive the formulas for herself.