Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.
Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance (ANOVA) and regression.
Charles "Chick" M. Judd is Professor of Distinction in the College of Arts and Sciences at the University of Colorado at Boulder. His research focuses on social cognition and attitudes, intergroup relations and stereotypes, judgment and decision making, and behavioral science research methods and data analysis. Gary H. McClelland is Professor of Psychology at the University of Colorado at Boulder. A Faculty Fellow at the Institute of Cognitive Science, his research interests include judgment and decision making, psychological models of economic behavior, statistics & data analysis, and measurement and scaling. Carey S. Ryan is a Professor in the Department of Psychology at the University of Nebraska at Omaha. She has research interests in stereotyping and prejudice, group processes, and program evaluation.
Inhaltsangabe
Preface 1. Introduction to Data Analysis 2. Simple Models: Definitions of Error and Parameter Estimates 3. Simple Models: Models of Error and Sampling Distributions 4. Simple Models: Statistical Inferences about Parameter Values 5. Simple Regression: Estimating Models with a Single Continuous Predictor 6. Multiple Regression: Models with Multiple Continuous Predictors 7. Moderated and Nonlinear Regression Models 8. One-Way ANOVA: Models with a Single Categorical Predictor 9. Factorial ANOVA: Models with Multiple Categorical Predictors and Product Terms 10. ANCOVA: Models with Continuous and Categorical Predictors 11. Repeated-Measures ANOVA: Models with Nonindependent Errors 12. Incorporating Continuous Predictors with Nonindependent Data: Towards Mixed Models 13. Outliers and Ill-Mannered Error 14. Logistic Regression: Dependent Categorical Variables References Appendix Author Index Subject Index
Preface 1. Introduction to Data Analysis 2. Simple Models: Definitions of Error and Parameter Estimates 3. Simple Models: Models of Error and Sampling Distributions 4. Simple Models: Statistical Inferences about Parameter Values 5. Simple Regression: Estimating Models with a Single Continuous Predictor 6. Multiple Regression: Models with Multiple Continuous Predictors 7. Moderated and Nonlinear Regression Models 8. One-Way ANOVA: Models with a Single Categorical Predictor 9. Factorial ANOVA: Models with Multiple Categorical Predictors and Product Terms 10. ANCOVA: Models with Continuous and Categorical Predictors 11. Repeated-Measures ANOVA: Models with Nonindependent Errors 12. Incorporating Continuous Predictors with Nonindependent Data: Towards Mixed Models 13. Outliers and Ill-Mannered Error 14. Logistic Regression: Dependent Categorical Variables References Appendix Author Index Subject Index
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Shop der buecher.de GmbH & Co. KG Bürgermeister-Wegele-Str. 12, 86167 Augsburg Amtsgericht Augsburg HRA 13309
