This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. The authors show how all analysis of variance and multiple regression can be accomplished within this framework. The model-comparison approach provides several benefits:
The book opens with an overview of data analysis. All the necessary concepts for statistical inference used throughout the book are introduced in Chapters 2 through 4. The remainder of the book builds on these models. Chapters 5 - 7 focus on regression analysis, followed by analysis of variance (ANOVA), mediational analyses, non-independent or correlated errors, including multilevel modeling, and outliers and error violations. The book is appreciated by all for its detailed treatment of ANOVA, multiple regression, nonindependent observations, interactive and nonlinear models of data, and its guidance for treating outliers and other problematic aspects of data analysis.
Intended for advanced undergraduate or graduate courses on data analysis, statistics, and/or quantitative methods taught in psychology, education, or other behavioral and social science departments, this book also appeals to researchers who analyze data. A protected website featuring additional examples and problems with data sets, lecture notes, PowerPoint presentations, and class-tested exam questions is available to adopters. This material uses SAS but can easily be adapted to other programs. A working knowledge of basic algebra and any multiple regression program is assumed.
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Charles "Chick" Judd is Professor of Distinction in the College of Arts and Sciences at the University of Colorado at Boulder. He received his Ph.D. in 1976 from Columbia University. A Fellow of the American Psychological Association, the Society of Personality and Social Psychology, and the Society for the Psychological Study of Social Issues, Dr. Judd’s research focuses on social cognition and attitudes, intergroup relations and stereotypes, judgment and decision making, and methods of behavioral science research and data analysis.
Gary McClelland is Professor of Psychology at the University of Colorado at Boulder. He received his Ph.D. in 1974 from The University of Michigan. A Faculty Fellow at the Institute of Cognitive Science, Dr. McClelland’s research interests include judgment and decision making, psychological models of economic behavior, statistics and data analysis, measurement and scaling, and mathematical psychology.
Carey S. Ryan is a Professor in the Department of Psychology at the University of Nebraska at Omaha. After earning her Ph.D. at the University of Colorado at Boulder, Professor Ryan taught at the University of Pittsburgh and joined the University of Nebraska faculty in 2001. She has research interests in stereotyping and prejudice, group processes, and program evaluation.
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Book Description Book Condition: New. Bookseller Inventory # 97808058338810000000
Book Description Routledge, 2008. Book Condition: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Introduction to Data Analysis. Simple Models: Definitions of Error and Parameter Estimates. Simple Models: Models of Error and Sampling Distributions. Simple Models: Statistical Inferences about Parameter Values. Simple Regression: Estimating Models with a Single Continuous Predictor. Multiple Regression: Models with Multiple Continuous Predictors. Moderated and Nonlinear Regression Models. One-Way ANOVA: Models with a Single Categorical Predictor. Factorial ANOVA: Models with Multiple Categorical Predictors and Product Terms. Models with Continuous and Categorical Predictors: ANCOVA. Repeated-Measures ANOVA: Models with Nonindependent Errors. Continuous Predictors with Nonindependent Observations. Outliers and Ill-Mannered Error. Bookseller Inventory # ABE_book_new_0805833889
Book Description Routledge. Book Condition: Brand New. Bookseller Inventory # 41807944
Book Description Routledge. Book Condition: New. Features many examples, insights and topics including mediational, categorical, and multilevel models of data analysis. This book focuses on regression analysis, followed by analysis of variance (ANOVA), mediational analyses, non-independent or correlated errors, including multilevel modeling, and outliers and error violations. Num Pages: 344 pages, 65 black & white illustrations, 107 black & white tables, 65 black & white line drawings. BIC Classification: JMB. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 264 x 186 x 21. Weight in Grams: 808. . 2008. 2nd Edition. Hardcover. . . . . Bookseller Inventory # V9780805833881
Book Description Routledge, 2016. Hardback. Book Condition: NEW. 9780805833881 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Print on Demand title, produced to the highest standard, and there would be a delay in dispatch of around 15 working days. Bookseller Inventory # HTANDREE0180169
Book Description 2008. Hardcover. Book Condition: New. 2nd. 178mm x 23mm x 254mm. Hardcover. This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition pr.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 344 pages. 0.771. Bookseller Inventory # 9780805833881
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