Applied Regression 2/e

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

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 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 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 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