Applied regression : an introduction
Author(s)
Bibliographic Information
Applied regression : an introduction
（Sage publications series, . Quantitative applications in the social sciences ; 07-22）
Sage, c2016
2nd ed
- : pbk
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Note
Includes bibliographical references (p. 99) and index
Description and Table of Contents
Description
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.
Table of Contents
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
by "Nielsen BookData"