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Statistical Models: Theory and Practice Paperback

ISBN-13: 978-0521743853 ISBN-10: 0521743850 Edition: 2nd

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Statistical Models: Theory and Practice + Statistical Models and Causal Inference: A Dialogue with the Social Sciences + Statistics, 4th Edition
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Product Details

  • Paperback: 456 pages
  • Publisher: Cambridge University Press; 2 edition (April 27, 2009)
  • Language: English
  • ISBN-10: 0521743850
  • ISBN-13: 978-0521743853
  • Product Dimensions: 9.5 x 6.8 x 0.9 inches
  • Shipping Weight: 1.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #103,657 in Books (See Top 100 in Books)

Editorial Reviews

Review

"At last, a second course in statistics that is serious, correct, and interesting. The book teaches regression, causal modeling, maximum likelihood, and the bootstrap. Everyone who analyzes real data should read this book, and we are extremely fortunate to now have the revised edition."
Persi Diaconis, Professor of Mathematics and Statistics, Stanford University

"A pleasure to read, this newly revised edition of Statistical Models shows the field's most elegant writer at the height of his powers. While most textbooks hurry past core assumptions in order to explicate technique, this book places the spotlight on the core assumptions, challenging readers to think critically about how they are invoked in practice."
Donald Green, Professor of Political Science, Yale University

"For three decades, David Freedman has been the conscience of statistics as applied to important scientific, policy, and legal issues. This book is his legacy, and it is our great good fortune to have the new edition. It should be required reading for any user of multivariate models -- statistician or otherwise -- whose ultimate concern is not with statistical technique but rather with the substantive conclusions, if any, licensed by the data and the analysis."
James M. Robins, Professor of Epidemiology and Biostatistics, Harvard School of Public Health

"Statistical models: theory and practice is lucid, helpful, insightful and a joy to read. It focuses on the most common tools of applied statistics with a clear and simple presentation. This revised edition organizes the chapters differently, making reading much easier. Moreover, it includes many new examples and exercises. In summary, it is a nice and extremely useful addition to the statistical literature."
Heleno Balfarine, Mathematical Reviews

Book Description

This lively and engaging textbook explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The author, David A. Freedman, explains the basic ideas of association and regression and takes you through the current models that link these ideas to causality.

More About the Author

David A. Freedman (1938-2008) was a Professor of Statistics at the University of California, Berkeley. A distinguished mathematical statistician, he revolutionized the teaching of statistics with his undergraduate (new edition, 2007) and graduate (new edition, 2009) textbooks that emphasize clear reasoning over mere technique and that use numerous illustrations and empirical examples that are vivid, real, and up-to-date. Freedman also published widely on the application--and misapplication--of statistics in the social sciences. This major aspect of his work is synthesized in his book "Statistical Models and Causal Inference" (2009). Freedman was a member of the American Academy of Arts and Sciences and in 2003 received the National Academy of Science's John J. Carty Award for his "profound contributions to the theory and practice of statistics."

Customer Reviews

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The writing style in this book is very clear.
Alexander C. Zorach
He provides exercises followed by detailed explanations of the correct answers.
Cynthia Taeuber
Note that this book assumes you are comfortable with linear algebra.
wanderer

Most Helpful Customer Reviews

50 of 50 people found the following review helpful By Alexander C. Zorach on November 24, 2007
Format: Paperback
This book is a very well-written, but ultimately fairly conventional textbook on linear models in statistics. It offers a very clear elementary introduction to the mathematics of the material, with an emphasis on both applications and rigor. It is to-the-point and does not cover very much material, instead choosing to cover material thoroughly and demonstrate the application of the material in practical situations.

I have heard this book described as "skeptical". It is not unduly skeptical; the author is just being the way every statistician ought to be. Any statistician who is not "skeptical" in this sense is accepting sloppy work.

The writing style in this book is very clear. Freedman is an outstanding writer! The book makes use of a decent amount of linear algebra and other mathematical notation that can be difficult for people to get through, but Freedman provides a very gentle introduction to the notation both through the text and through exercises (broken into small pieces, with a smooth gradient of difficulty). If you take your time and work through the book, you will not find it difficult to read.

Still, this book is not the be-all and end-all of texts on statistical models. It is particularly lacking on philosophical depth when it comes to the mathematical theory. This book describes techniques that are common practice and teaches you how to use them properly and evaluate them critically. It does not probe very deeply into how or why these techniques were developed. It does not encourage the reader to question the techniques themselves or to create new techniques or new theory. In my opinion, this is a shortcoming worth mentioning.

Also, there are a wide variety of topics that this book seems to ignore.
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73 of 76 people found the following review helpful By N N Taleb on May 2, 2007
Format: Paperback
The Best Statistics Book I've Seen

I spent my life focusing on the errors of statistics and how they sometimes fail us in real life, because of the misinterpretation of what the techniques can do for you. This book is outstanding in the following two aspects: 1) It is of immense clarity, embedding everything in real situations, 2) It uses the real-life situation to critique the statistical model and show you the limit of statistic. For instance, he shows a few anecdotes here and there to illustrate how correlation between two variables might not mean anything causal, or how asymptotic properties may not be relevant in real life.

This is the first statistics book I've seen that cares about presenting statistics as a tool to GET TO THE TRUTH.

Please buy it.

Nassim Nicholas Taleb
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32 of 33 people found the following review helpful By Michele Abernathy on July 15, 2006
Format: Hardcover
The formal reviews say this book is very well written. That is an understatement. Freedman uses plain English and interesting examples to explain the concepts behind the statistical jargon. This book is certainly good for those who will go on to advanced statistics and those who can read mathematical notation more easily than words. For those of us who need to apply the results of statistical studies but who do not wish to gain graduate degrees in statistics, Freedman gives us the background to understand studies we have to use, an understanding of whether regression is an appropriate model for specific situations, and the tools to ensure we are making appropriate comparisons. This book IS well written because it leads to understanding concepts rather than mechanical memorization.
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12 of 12 people found the following review helpful By Michael R. Chernick on March 30, 2010
Format: Paperback Verified Purchase
The late Professor David A. Freedman possessed the rare skill of being at the top of his profession in both theoretical and applied statistics. His introductory text with the simple title "Statistics" has been praised as one of the best ever written. On the other side he could write very deep mathematical books as was demonstrated in his trilogy on Markov processes and diffusions. In the real world he contributed to the application of critical thinking about the pros and cons of statistical models and was steadfast in his position against the adjustment of the decennial US Census even though most prominent statisticians stood on the other side. He did consulting which grounded him into real applications particularly in Econometrics. As a Berkeley professor he collaborated with many of the top theoretical statisticians in the world. Many of which were at Berkeley or Stanford.

I concur with the enthusiasm for this book that is shown by the other 4 customer reviews. Persi Diaconis from Stanford was a long-time collaborator with Freedman and the late Erich Lehmann long-time Berkeley colleague. I think the praise for this book shown by them is far more important to hear that some of the nice things I might say.

Diaconis: "At last, a second course in statistics that is serious, correct, and interesting. The book teaches regression, causal mdoeling, maximum likelihood, and the bootstrap. Everyone who analyzes real data should read this book."

Lehmann: "This book is outstanding for clarity of its thought and writng. It prepares readers for a critical assessment of the technical literature in the social and health sciences, and it provides a welcome antidote to the standard formulaic approach to statistics.
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