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Applied Regression
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Artikel-Nr:
9781483381497
Veröffentl:
2015
Einband:
EPUB
Seiten:
120
Autor:
Colin Lewis-Beck
Serie:
Quantitative Applications in the Social Sciences
eBook Typ:
EPUB
eBook Format:
Reflowable EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:
Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.
Known for its readability and clarity, thisSecond Edition of the best-sellingApplied 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.
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
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