A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science)

 
9781420062014: A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science)

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.

With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss–Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers.

This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.

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Monahan, John F.
Published by Taylor Francis Ltd, United States (2008)
ISBN 10: 1420062018 ISBN 13: 9781420062014
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Book Description Taylor Francis Ltd, United States, 2008. Paperback. Book Condition: New. New.. 234 x 152 mm. Language: English . Brand New Book. A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss-Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers. This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models. Bookseller Inventory # AAZ9781420062014

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Monahan, John F.
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Book Description Chapman and Hall/CRC 2008-04-21, 2008. Book Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Bookseller Inventory # NU-GRD-03031911

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Monahan, John F.
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Book Description Taylor Francis Ltd, United States, 2008. Paperback. Book Condition: New. New.. 234 x 152 mm. Language: English . Brand New Book. A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss-Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers. This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models. Bookseller Inventory # AAZ9781420062014

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Book Description Book Condition: New. Bookseller Inventory # ST1420062018. Bookseller Inventory # ST1420062018

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Monahan, John F.
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Book Description Taylor & Francis Ltd 2008-03-31, 2008. paperback. Book Condition: New. Bookseller Inventory # 9781420062014

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Monahan, John F.
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Book Description Chapman and Hall/CRC, 2008. Book Condition: New. Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Preface. Examples of the General Linear Model. The Linear Least Squares Problem. Estimability and Least Squares Estimators. Gauss-Markov Model. Distributional Theory. Statistical Inference. Further Topics in Testing. Variance Components and Mixed Models. The Multivariate Linear Model. Appendices. Bibliography. Bookseller Inventory # ABE_book_new_1420062018

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Book Description Paperback. Book Condition: New. Not Signed; A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theo. book. Bookseller Inventory # ria9781420062014_rkm

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Book Description Chapman and Hall/CRC, 2008. Book Condition: New. Employing non-full-rank design matrices throughout, this book enables understanding of basic linear models. This book introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss-Markov model. Series: Chapman & Hall/CRC Texts in Statistical Science. Num Pages: 304 pages, 6 black & white illustrations, 2 black & white tables. BIC Classification: PBT. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 230 x 157 x 17. Weight in Grams: 464. . 2008. 1st Edition. Paperback. . . . . . Bookseller Inventory # V9781420062014

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Book Description Routledge, 2008. Paperback. Book Condition: New. Brand New Book. Shipping: Once your order has been confirmed and payment received, your order will then be processed. The book will be located by our staff, packaged and despatched to you as quickly as possible. From time to time, items get mislaid en route. If your item fails to arrive, please contact us first. We will endeavour to trace the item for you and where necessary, replace or refund the item. Please do not leave negative feedback without contacting us first. All orders will be dispatched within two working days. If you have any quesions please contact us. Bookseller Inventory # V9781420062014

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Book Description Chapman and Hall/CRC. Book Condition: New. Employing non-full-rank design matrices throughout, this book enables understanding of basic linear models. This book introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss-Markov model. Series: Chapman & Hall/CRC Texts in Statistical Science. Num Pages: 304 pages, 6 black & white illustrations, 2 black & white tables. BIC Classification: PBT. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 230 x 157 x 17. Weight in Grams: 464. . 2008. 1st Edition. Paperback. . . . . Books ship from the US and Ireland. Bookseller Inventory # V9781420062014

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