BUNDLE: Weis: Introduction to Abnormal Child and Adolescent Psychology 2e + Wilmshurst: Child and Adolescent Psychopathology 3e
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Product details:
- Edition number Second Edition
- Publisher SAGE Publications, Inc
- Date of Publication 8 September 2015
- ISBN 9781483369976
- Binding Unidentified
- No. of pages120 pages
- Size 215x139 mm
- Language English 0
Categories
Short description:
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.
MoreLong 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.
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!
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
