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Linear models with R /

Faraway, Julian James.

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Linear models with R /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Linear models with R // Julian J. Faraway.
Author:	Faraway, Julian James.
Published:	Boca Raton, FL :CRC Press, : 2015.,
Description:	xii, 274 p. :ill. ;25 cm.
Subject:	Analysis of variance. -
ISBN:	9781439887332

Linear models with R /
Faraway, Julian James.

Linear models with R /Julian J. Faraway. - Second edition. - Boca Raton, FL :CRC Press,2015. - xii, 274 p. :ill. ;25 cm. - Chapman & Hall/CRC texts in statistical science series.. - Texts in statistical science.

Includes bibliographical references and index.

Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition. New to the Second Edition, Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality, Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates, Extensive use of the ggplot2 graphics package in addition to base graphics, Like its widley praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to- date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R. Features, Demonstrates the flexibility of linear models in many examples, Assumes basic knowledge of R and statistics, Emphasizes intuition over rigorous proofs, Presents exercises at the end of each chapter, Includes datasets and R commands Book jacket.

ISBN: 9781439887332GBP57.99

LCCN: 2014015948Subjects--Topical Terms:

516400
Analysis of variance.

LC Class. No.: QA279 / .F37 2015

Dewey Class. No.: 519.5/3802855133

Linear models with R /
LDR:02207cam a2200193 a 4500 001 1979279
008 150513s2015 flua b 001 0 eng
010 $a 2014015948
020 $a 9781439887332 $q (hbk.) : $c GBP57.99
020 $a 1439887330 $q (hbk.)
040 $a DLC $b eng
050 0 0 $a QA279 $b .F37 2015
082 0 0 $a 519.5/3802855133 $2 23
100 1 $a Faraway, Julian James. $3 1535970
245 1 0 $a Linear models with R / $c Julian J. Faraway.
250 $a Second edition.
260 # $a Boca Raton, FL : $b CRC Press, $c 2015.
300 $a xii, 274 p. : $b ill. ; $c 25 cm.
490 1 0 $a Chapman & Hall/CRC texts in statistical science series.
504 $a Includes bibliographical references and index.
520 # $a Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition. New to the Second Edition, Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality, Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates, Extensive use of the ggplot2 graphics package in addition to base graphics, Like its widley praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to- date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R. Features, Demonstrates the flexibility of linear models in many examples, Assumes basic knowledge of R and statistics, Emphasizes intuition over rigorous proofs, Presents exercises at the end of each chapter, Includes datasets and R commands Book jacket.
650 # 0 $a Analysis of variance. $3 516400
650 # 0 $a Regression analysis. $3 529831
830 0 $a Texts in statistical science $3 2121397