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Applied Regression
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Applied Regression
An Introduction

Second Edition
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July 2015 | 120 pages | SAGE Publications, Inc
Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. The authors then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.

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Series Editor's Introduction
 
Preface
 
Acknowledgments
 
About the Authors
 
1. Bivariate Regression: Fitting a Straight Line
 
2. Bivariate Regression: Assumptions and Inferences
 
3. Multiple Regression: The Basics
 
4. Multiple Regression: Special Topics
 
Appendix
 
References
 
Index

Supplements

This is a great book to acquaint students with the world of linear models. It is perfect to use in combination with other texts, or as a stand-along book in introductory courses. The Lewis-Beck’s have updated the presentation, provided additional examples, and included more discussion of regression diagnostics. I am sure that it will, once again, be a best seller!

Saundra K. Schneider
Michigan State University

This is an excellent update and extension of a wonderfully clear exposition of bivariate and multiple regression analysis for beginning practitioners and students.  I was a fan of the first edition, and I am even more pleased with the revision.  

Walter J. Stone
University of California, Davis

This is one of the best resources on basic regression techniques available on the market today and it remains my go-to guide for my own research. Applied Regression is the quintessential text for graduate students pursuing degrees in the quantitative social sciences; it has helped train several generations of social science researchers over the course of the last four decades. The second edition will remain instrumental in training social scientists for years to come.

Matt Vogel
University of Missouri - St. Louis

The new edition of Applied Regression maintains the excellence of the original edition while modernizing and extending it.  Its highpoint is how the Lewis-Becks state everything with complete precision.  From the assumptions of OLS to the ways of coping with outliers and to the methods of detecting multicollinearity, the authors tell readers exactly what they need to know to perform regression analysis.

Herbert Weisberg
The Ohio State University

I teach advanced research methods in psychology at the undergraduate level. This text only applies to some of my students, depending upon their research project/ design. Therefore, I recommend it to those who should do regression analyses with their data.

Dr Angela Birt
Psychology, Mount St Vincent University
April 7, 2016

Basic, uncomplicated introduction to regression for students in a professional degree program.

Dr Lizabeth Kay Kleintop
Economics Business Dept, Moravian College
February 12, 2016
Key features

NEW TO THIS EDITION:

  • Updated and improved graphs and graphical examples have a more contemporary design, having been created in the R software.
  • New applied examples of transformations are included, with a focus on solving problems of nonlinearity or outliers.
  • Expanded coverage of statistical methods includes more on regression assumptions and model fit, additional material on residual analysis, and inclusion of the measures of tolerance and VIF in the discussion of collinearity.
  • More visual illustrations clarify discussion of the differences between linearity and nonlinearity.
  • A mathematical notation that conforms to more current style.

 KEY FEATURES:

  • The content is accessible, requiring no advanced math training (beyond high school level) for comprehension.
  • Information is organized logically in a way that students find it easy to follow.
  • The book is concise and can be digested quickly for the basics behind the OLS model.

Sample Materials & Chapters

Lewis-Beck Data Files

Chapter 1


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