Introduction to Linear Models and Statistical Inference

Janke, Steven J.; Tinsley, Frederick

ISBN 10: 0471662593 ISBN 13: 9780471662594
Edité par Wiley-Interscience, 2005
Neuf(s) Couverture rigide

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A multidisciplinary approach that emphasizes learning by analyzing real-world data sets

This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science.

As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including:
* Simple linear models
* Multivariate models
* Model building
* Analysis of variance (ANOVA)
* Analysis of covariance (ANCOVA)
* Logistic regression
* Total least squares

The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed.

Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding.

The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models.

With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.

À propos de l?auteur: STEVEN J. JANKE, PHD, and FREDERICK C. TINSLEY, PHD, are both Professors of Mathematics at Colorado College, Colorado Springs. Both Dr. Janke and Dr. Tinsley have been teaching linear models courses for more than two decades.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Détails bibliographiques

Titre : Introduction to Linear Models and ...
Éditeur : Wiley-Interscience
Date d'édition : 2005
Reliure : Couverture rigide
Etat : New

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Janke, Steven J.; Tinsley, Frederick C.
Edité par Wiley-Interscience, New York, 2005
ISBN 10 : 0471662593 ISBN 13 : 9780471662594
Ancien ou d'occasion Couverture rigide

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Janke, Steven J.; Tinsley, Frederick
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Janke, Steven J.; Tinsley, Frederick
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Steven J. Janke|Frederick Tinsley
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Gebunden. Etat : New. STEVEN J. JANKE, PHD, and FREDERICK C. TINSLEY, PHD, are both Professors of Mathematics at Colorado College, Colorado Springs. Both Dr. Janke and Dr. Tinsley have been teaching linear models courses for more than two decades.A multidisciplinary approach. N° de réf. du vendeur 446917651

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Janke, Steven J.; Tinsley, Frederick C.
Edité par Wiley-Interscience, 2005
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Neuf Couverture rigide

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Frederick Tinsley
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Janke, Steven J.; Tinsley, Frederick C.
Edité par Wiley-Interscience, 2005
ISBN 10 : 0471662593 ISBN 13 : 9780471662594
Neuf Couverture rigide

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Steven J. Janke
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Hardcover. Etat : new. Hardcover. A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences. A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780471662594

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Hardcover. Etat : new. Hardcover. A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences. A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780471662594

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