Lewis-Beck, Colin
Applied regression : an introduction Colin, Lewis-Beck, Michael S. Lewis-Beck - 2nd ed. - Los Angeles : Sage, c2016. - xvi, 103 p. : ill ; 21 cm. - Quantitative applications in the social sciences ; Vol. no. 07-022 .
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.
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.
9781483381473
2015011813
Regression analysis
519.5/36
Applied regression : an introduction Colin, Lewis-Beck, Michael S. Lewis-Beck - 2nd ed. - Los Angeles : Sage, c2016. - xvi, 103 p. : ill ; 21 cm. - Quantitative applications in the social sciences ; Vol. no. 07-022 .
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.
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.
9781483381473
2015011813
Regression analysis
519.5/36