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Sinopsis
This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model.
The text describes the foundational logic of the unified model comparison framework. It then shows how this framework can be applied to increasingly complex models including multiple continuous and categorical predictors, as well as product predictors (i.e., interactions and nonlinear effects). The text also describes analyses of data that violate assumptions of independence, homogeneity, and normality. The analysis of nonindependent data is treated in some detail, covering standard repeated measures analysis of variance and providing an integrated introduction to multilevel or hierarchical linear models and logistic regression.
Highlights of the fourth edition include:
- Expanded coverage of generalized linear models and logistic regression in particular
- A discussion of power and ethical statistical practice as it relates to the replication crisis
- An expanded collection of online resources such as PowerPoint slides and test bank for instructors, additional exercises and problem sets with answers, new data sets, practice questions, and R code
Clear and accessible, this text is intended for advanced undergraduate and graduate level courses in data analysis.
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Joshua Correll is a professor of psychology and neuroscience in the College of Arts and Sciences at the University of Colorado at Boulder. His research examines face processing, stereotypes and data analysis.
Abigail (Abby) M. Folberg is an assistant professor of psychology in the College of Arts and Sciences at the University of Nebraska at Omaha. Her research examines the impacts of stereotypes and prejudice on marginalized group members as well as how individuals and organizations can reduce prejudice and discrimination.
Charles “Chick” M. Judd is Professor Emeritus 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 Emeritus 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 and data analysis, and measurement and scaling.
Carey S. Ryan is Professor Emeritus in the Department of Psychology at the University of Nebraska at Omaha. Her research interests include stereotyping and prejudice, group processes, and program evaluation.
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Data Analysis
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Joshua Correll is a professor of psychology and neuroscience in the College of Arts and Sciences at the University of Colorado at Boulder. His research examines face processing, stereotypes and data analysis.Abigail (Abby) M. Folberg. Nº de ref. del artículo: 2151939395
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Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
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Data Analysis: A Model Comparison Approach to Regression, Anova and Beyond
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Paperback. Condición: Brand New. 4th edition. 478 pages. 10.00x7.00 inches. In Stock. This item is printed on demand. Nº de ref. del artículo: __1032572086
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Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
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Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
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Data Analysis (Paperback)
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ISBN 13: 9781032572086
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Paperback. Condición: new. Paperback. This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model.The text describes the foundational logic of the unified model comparison framework. It then shows how this framework can be applied to increasingly complex models including multiple continuous and categorical predictors, as well as product predictors (i.e., interactions and nonlinear effects). The text also describes analyses of data that violate assumptions of independence, homogeneity, and normality. The analysis of nonindependent data is treated in some detail, covering standard repeated measures analysis of variance and providing an integrated introduction to multilevel or hierarchical linear models and logistic regression.Highlights of the fourth edition include:Expanded coverage of generalized linear models and logistic regression in particularA discussion of power and ethical statistical practice as it relates to the replication crisisAn expanded collection of online resources such as PowerPoint slides and test bank for instructors, additional exercises and problem sets with answers, new data sets, practice questions, and R codeClear and accessible, this text is intended for advanced undergraduate and graduate level courses in data analysis. This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9781032572086
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Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
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Data Analysis (Paperback)
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ISBN 10: 1032572086
ISBN 13: 9781032572086
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Paperback. Condición: new. Paperback. This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model.The text describes the foundational logic of the unified model comparison framework. It then shows how this framework can be applied to increasingly complex models including multiple continuous and categorical predictors, as well as product predictors (i.e., interactions and nonlinear effects). The text also describes analyses of data that violate assumptions of independence, homogeneity, and normality. The analysis of nonindependent data is treated in some detail, covering standard repeated-measures analysis of variance and providing an integrated introduction to multilevel or hierarchical linear models and logistic regression.Highlights of the fourth edition include:Expanded coverage of generalized linear models and logistic regression in particularA discussion of power and ethical statistical practice as it relates to the replication crisisAn expanded collection of online resources such as PowerPoint slides and test bank for instructors, additional exercises and problem sets with answers, new data sets, practice questions, and R codeClear and accessible, this text is intended for advanced undergraduate and graduate level courses in data analysis. This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781032572086
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Data Analysis : A Model Comparison Approach to Regression, ANOVA, and Beyond
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This essential textbook provides an integrated treatment of data analysis for the social and behavioral sciences. It covers all the key statistical models in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Nº de ref. del artículo: 9781032572086
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Data Analysis: A Model Comparison Approach to Regression, Anova and Beyond
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Paperback. Condición: Brand New. 4th edition. 478 pages. 10.00x7.00x10.00 inches. In Stock. Nº de ref. del artículo: x-1032572086
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