Linear Models in Statistics (Wiley Series in Probability and Statistics)

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9780471754985: Linear Models in Statistics (Wiley Series in Probability and Statistics)

Book by Rencher Alvin C Schaalje G Bruce

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"This indeed clearly written book will do great service for advanced undergraduate and also for PhD students." (International Statistical Review, Dec 2008) "This well-written book represents various topics on linear models with great clarity in an easy-to-understand style." (CHOICE, Aug 2008)

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The essential introduction to the theory and application of linear models-now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features:* New chapters on Bayesian linear models as well as random and mixed linear models* Expanded discussion of two-way models with empty cells* Additional sections on the geometry of least squares* Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS(r) code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

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Rencher, Alvin C.;Schaalje, G. Bruce
Editorial: Wiley-Interscience (2008)
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción Wiley-Interscience, 2008. Hard Cover. Estado de conservación: New. New. Mint condition US Edition. 2 Ed. Select Expedited to get your book in 3 to 5 business days including USA, CANADA, AUSTRALIA. All packages can be tracked. Excellent service. Thank you for looking. Nº de ref. de la librería 001671

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Rencher, Alvin C.;Schaalje, G. Bruce
Editorial: Hoboken, New Jersey, U.S.A.: Wiley-Interscience (2008)
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción Hoboken, New Jersey, U.S.A.: Wiley-Interscience, 2008. Hardcover. Estado de conservación: New. Ship out 24 hours,Brand new,US edition, (Express shipping worldwide)2-4 biz days delivery to worldwide Same shipping fee with US, Canada,Europe country, Australia, item will ship out from either USA or Asia. Nº de ref. de la librería ABE-6337107610

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Rencher, Alvin C., Schaalje, G. Bruce
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ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción Wiley-Interscience, 2008. Hardcover. Estado de conservación: New. Nº de ref. de la librería P110471754986

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Alvin C. Rencher, G. Bruce Schaalje
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ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción Wiley-Interscience, 2008. Hardcover. Estado de conservación: New. 2. Nº de ref. de la librería DADAX0471754986

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Alvin C. Rencher (Brigham Young Univ., Provo, Utah); G. Bruce Schaalje (Brigham Young Univ., Provo, UT)
Editorial: John Wiley and Sons
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción John Wiley and Sons. Estado de conservación: New. Brand New. Nº de ref. de la librería 0471754986

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Alvin C. Rencher
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Descripción Wileyand#8211;Blackwell, 2008. HRD. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería FW-9780471754985

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Alvin C. Rencher, G. Bruce Schaalje
Editorial: John Wiley and Sons Ltd, United Kingdom (2008)
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción John Wiley and Sons Ltd, United Kingdom, 2008. Hardback. Estado de conservación: New. 2nd Revised edition. 239 x 160 mm. Language: English . Brand New Book. The essential introduction to the theory and application of linear models-now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression.Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features:* New chapters on Bayesian linear models as well as random and mixed linear models* Expanded discussion of two-way models with empty cells* Additional sections on the geometry of least squares* Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS(r) code for all numerical examples.Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance. Nº de ref. de la librería AAH9780471754985

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8.

Alvin C. Rencher, G. Bruce Schaalje
Editorial: John Wiley and Sons Ltd, United Kingdom (2008)
ISBN 10: 0471754986 ISBN 13: 9780471754985
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The Book Depository US
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Descripción John Wiley and Sons Ltd, United Kingdom, 2008. Hardback. Estado de conservación: New. 2nd Revised edition. 239 x 160 mm. Language: English . Brand New Book. The essential introduction to the theory and application of linear models-now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression.Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features:* New chapters on Bayesian linear models as well as random and mixed linear models* Expanded discussion of two-way models with empty cells* Additional sections on the geometry of least squares* Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS(r) code for all numerical examples.Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance. Nº de ref. de la librería AAH9780471754985

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Alvin C. Rencher; G. Bruce Schaalje
Editorial: Wiley-Interscience (2008)
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción Wiley-Interscience, 2008. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería 0471754986

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Rencher, Alvin C.
ISBN 10: 0471754986 ISBN 13: 9780471754985
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Descripción 2008. HRD. Estado de conservación: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Nº de ref. de la librería KB-9780471754985

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