Known for its readability and clarity, this Second Edition 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. 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
Applied Regression: An Introduction
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