{"product_id":"linear-models-with-r-hardcover","title":"Linear Models with R - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJulian J. Faraway\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cem\u003eA Hands-On Way to Learning Data Analysis\u003c\/em\u003e\u003c\/p\u003e\u003cp\u003ePart 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. \u003cstrong\u003eLinear Models with R, Second Edition\u003c\/strong\u003e 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.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eNew to the Second Edition\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eReorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality \u003c\/li\u003e \u003cli\u003eAdditional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates\u003c\/li\u003e \u003cli\u003eExtensive use of the ggplot2 graphics package in addition to base graphics \u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eLike its widely 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.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 286\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.7 x 9.6 x 6.3 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 01, 2014\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47336875360505,"sku":"9781439887332","price":186.3,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/OERDbTFvWDROSEtpNmdtSGVHSHJ2UT09.webp?v=1769671449","url":"https:\/\/bookscloud.io\/products\/linear-models-with-r-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}