Linear Models with R av Julian J. (University of Bath United Kingdom) Faraway

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<P><EM>A Hands-On Way to Learning Data Analysis</EM></P><P></P><P>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. <STRONG>Linear Models with R, Second Edition</STRONG> 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.</P><P><STRONG>New to the Second Edition</STRONG></P><UL><P><LI>Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality </LI><LI>Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates</LI><LI>Extensive us