9780805833881

Data Analysis: A Model Comparison Approach, Second Edition

Charles M. Judd; Gary H. McClelland; Carey S. Ryan

ISBN 10: 0805833889 / 0-8058-3388-9
ISBN 13: 9780805833881
Publisher: Routledge
Publication Date: 2008
Binding: Hardcover
Editorial Reviews:
Synopsis:

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:

  • It strengthens the intuitive understanding of the material thereby increasing the ability to successfully analyze data in the future
  • It provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of questions
  • It reduces the number of statistical techniques that must be memorized
  • It teaches readers how to become data analysts instead of statisticians.

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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Data Analysis (ISBN: 0805833889 / 0-8058-3388-9)
Charles M. Judd;Gary H. McClelland;Carey S. Ryan
ISBN 10: 0805833889
ISBN 13: 9780805833881
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Data Analysis: A Model Comparison Approach (Hardback) (ISBN: 9780805833881)
Charles M. Judd;Gary H. McClelland;Carey S. Ryan
ISBN 10: 0805833889
ISBN 13: 9780805833881
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Book Description: Taylor Francis Inc, United States, 2008. Hardback. Book Condition: New. 2nd Revised edition. 254 x 178 mm. Brand New Book. 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: It strengthens the intuitive understanding of the material thereby increasing the ability to successfully analyze data in the future It provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of questions It reduces the number of statistical techniques that must be memorized It teaches readers how to become data analysts instead of statisticians. 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. Bookseller Inventory # AA69780805833881

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Data Analysis: A Model Comparison Approach (Hardback) (ISBN: 9780805833881)
Charles M. Judd;Gary H. McClelland;Carey S. Ryan
ISBN 10: 0805833889
ISBN 13: 9780805833881
Bookseller: The Book Depository (Gloucester, UK, United Kingdom)
Bookseller Rating: 5-star rating
Quantity Available: 10

Book Description: Taylor Francis Inc, United States, 2008. Hardback. Book Condition: New. 2nd Revised edition. 254 x 178 mm. Brand New Book. 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: It strengthens the intuitive understanding of the material thereby increasing the ability to successfully analyze data in the future It provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of questions It reduces the number of statistical techniques that must be memorized It teaches readers how to become data analysts instead of statisticians. 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. Bookseller Inventory # AA69780805833881

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Data Analysis (ISBN: 9780805833881)
Charles M. Judd;Gary H. McClelland;Carey S. Ryan
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Data Analysis: A Model Comparison Approach (Hardcover) (ISBN: 0805833889 / 0-8058-3388-9)
Charles M. Judd;Gary H. McClelland;Carey S. Ryan
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ISBN 13: 9780805833881
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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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Charles M. Judd;Gary H. McClelland;Carey S. Ryan
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Charles M. Judd;Gary H. McClelland;Carey S. Ryan
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Charles M. Judd;Gary H. McClelland;Carey S. Ryan
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