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The strength of this text is the unified presentation of several regression topics that provides the student with a global perspective on regression analysis. The student is well served with this unified approach as it facilitates deeper research on any one topic with more advanced texts.
This text is a one-stop shop for me for my first year stats sequence for students in our program. Those wanting the technical detail will be satisfied; those wanting an excellent explanation of these methods using real-world examples and approachable language will also be satisfied.
I have enjoyed using previous editions of this text and look forward to using this edition. It covers all key topics, and quite a few advanced ones, in one well-written text.
PRAISE FOR THE PREVIOUS EDITIONS
In summary, this is an excellent text on regression applications and methods, written with authority, lucidity, and eloquence. The second edition provides substantive and topical updates, and makes the book suitable for courses designed to emphasize both the classical and the modern aspects of regression.
Even though the book is written with social scientists as the target audience, the depth of material and how it is conveyed give it far broader appeal. Indeed, I recommend it as a useful learning text and resource for researchers and students in any field that applies regression or linear models (that is, most everyone), including courses for undergraduate statistics majors…. The author is to be commended for giving us this book, which I trust will find a wide and enduring readership.
[T]his wonderfully comprehensive book focuses on regression analysis and linear models… We enthusiastically recommend this book—having used it in class, we know that it is thorough and well-liked by students.
I loved it and students did too (well, as much as they will!)
The book covers regression only and not all the topics in regression. I need a book that covers both regression methods and design of experiments methods.