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7 of 7 people found the following review helpful
5.0 out of 5 stars A Fantastic Text for Anyone Interested in Deeply Analyzing Data
This book is a fantastic graduate-level data analysis (statistics) text. The writing style is clear and compelling. It is ideal for the scientist/researcher who want to ask practical questions of their data without being forced into standard statistical recipes. I have been searching for a statistics text like this for nearly 10 years and am very pleased to have found...
Published on November 21, 2009 by C. Long

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1 of 1 people found the following review helpful
3.0 out of 5 stars Excellent book, flaws with the kindle edition
This is an excellent book. Their approach to explaining the statistical analysis is in my opinion one of the best I've seen. My only complaint is with the kindle edition of this book. There are several places in the text where the symbols don't display correctly. I've also encounter a couple paragraphs repeated twice and one instance of the wrong equation being displayed...
Published 15 months ago by Ben


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7 of 7 people found the following review helpful
5.0 out of 5 stars A Fantastic Text for Anyone Interested in Deeply Analyzing Data, November 21, 2009
This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
This book is a fantastic graduate-level data analysis (statistics) text. The writing style is clear and compelling. It is ideal for the scientist/researcher who want to ask practical questions of their data without being forced into standard statistical recipes. I have been searching for a statistics text like this for nearly 10 years and am very pleased to have found it.
The book focuses you, the reader, on composing powerful, but simply-formed models of the questions you wish to ask of your data. It builds a unified approach to data analysis from first principles rather than presenting the typical hodge-podge of cookbook techniques found in many traditional statistics texts. Instead of trying to fit your data into a recipe (t-test, ANOVA, regression, ANCOVA, etc.) you specify a pair (or multiple pairs) of model equations and then use them to ask quantitative questions of your data. Thus, you spend your time asking questions of your data not forcing it into some pre-determined recipe which may be an ill fit. In addition to answering standard "recipe" questions, with this approach you can easily generate and answer questions that fall between the standard recipes, but that are quite valid to ask.
The text presents exactly as much math as necessary to understand the tools, but not more: it does not require a heavy mathematical background. The authors use the text in a graduate level psychology class, but it the book is applicable to those with a more or less quantitative background.

I highly recommend this book to anyone interested in a deep analysis of whatever data might cross your desk.
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2 of 2 people found the following review helpful
5.0 out of 5 stars From someone who "ate the dogfood"... WOOF!!!, November 12, 2011
By 
Brad Aisa "rational realist" (Boulder, CO United States) - See all my reviews
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This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
I'm not going to write a long review of the book itself because C. Long expressed the immense virtues of this book perfectly--I just wanted to share my experience with it.

I was a student of Drs. Judd and McClelland in a year-long graduate level stats (oops! "Data analysis") course. Although this was nominally a Psychology course, its qualities were so famous that people came from departments all over the University to take it, such as Education, Science, Business, and others. I've taken stats a number of times over the years, and never really "got it"--it was all so mysterious with all these seemingly different test types. This was the first course in which I actually completely understood the underlying concepts! Believe it or not, it made statistics and data analysis exciting! I haven't actually used these techniques now in a couple of years, but have recently had need to brush up and start using them again. All the basic concepts are as fresh in my mind as the year I took this course, and I'm confident I'll be up to speed very quickly with just a quick refresh browse of the book.

I can't recommend this text highly enough!

P.S. Oh, yeah... yes, I got an "A"... ;)
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1 of 1 people found the following review helpful
3.0 out of 5 stars Excellent book, flaws with the kindle edition, September 20, 2013
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This is an excellent book. Their approach to explaining the statistical analysis is in my opinion one of the best I've seen. My only complaint is with the kindle edition of this book. There are several places in the text where the symbols don't display correctly. I've also encounter a couple paragraphs repeated twice and one instance of the wrong equation being displayed (the equation itself wasn't wrong it was just that a different equation should have appeared in its place). If you are familiar with basic statistics I don't think any of these issues will really hinder your understanding. I recommend the book overall, and personally I would buy the kindle edition again purely for the convince of it.
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4.0 out of 5 stars Excellent book with a buggy kindle edition, March 25, 2014
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This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
I loved this book. I've struggled with stats in a number of classes before but this one finally clicked. The focus on model comparisons as a unifying framework means that everything builds neatly on everything else and ties together in predictable ways. Other stats classes have thrown grab bags of ideas and formulae at you but this book does a great job of showing how there is really only one true formula and everything is either an estimate of that formula or trying to make it apply only to a specific situation instead of a more general form.

My two qualms with it are that the language used is different from what many other stats books use so it can be tough to find other resources online and problems with the kindle edition. Sometimes the wrong formulae is present, sometimes it can't correctly render special characters, and other little problems like that.
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4.0 out of 5 stars Helpful For Someone Who Has Never Learned Stats Before, February 10, 2014
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This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
I have found that the prevailing method of learning stats, where you learn what kinds of tests work best for which kinds of data, kind of conflicts with this book. This means that if you've already learned stats before, and are now going back for another try, this will be different for you. Like switching from PC to Mac. But I think for those who have never learned stats, this approach will be easier to understand and provide a much more conceptually satisfying foundation for understanding statistical methods.

On an unrelated note, I do feel compelled to comment that I dislike how frequently the authors use the terms "of course", "obviously" and even "it should be obvious that" when instructing the reader. I am not sure what value the authors thought these phrases would have in a book intended for novices, other than to make the reader feel kind of dumb if they didn't know the information that was "obvious".
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5.0 out of 5 stars Clear, systematic approach to understanding data analysis, November 6, 2013
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This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
Clear, easy to read but includes critical information needed to understand data analysis.
The authors' approach is systematic but does require a basic understanding of the statistics.
The graphs make it easier to understand the internal working of what the statistics express.
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5.0 out of 5 stars An extremely interesting and well writen book, December 9, 2012
By 
Gastón Pezzuchi (La Plata, Buenos Aires Argentina) - See all my reviews
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It is an extremely interesting approach to data analysis, and a true must have in almost any specialized collection of statistical books.
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4.0 out of 5 stars Got a soft-cover one, September 19, 2014
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This review is from: Data Analysis: A Model Comparison Approach, Second Edition (Hardcover)
The book is fine, but it is curious that I got an soft cover one?
My classmates all order this book here, but they all got hardcover ones.
But that's OK, it's much lighter to carry it to class.
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Data Analysis: A Model Comparison Approach, Second Edition
Data Analysis: A Model Comparison Approach, Second Edition by Charles M. Judd (Hardcover - August 29, 2008)
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