A Hands-On Way to Learning Data Analysis
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
Like 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.
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Julian J. Faraway
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Da: -OnTimeBooks-, Phoenix, AZ, U.S.A.
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Da: Solr Books, Lincolnwood, IL, U.S.A.
Condizione: good. This book is in Good condition. There may be some notes and highligting but otherwise the book is in overall good condition. Codice articolo BCV.1439887330.G
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Da: BookHolders, Towson, MD, U.S.A.
Condizione: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: SOME ] [ Edition: Second ] Publisher: Routledge Pub Date: 7/1/2014 Binding: Hardcover Pages: 286 Second edition. Codice articolo 6884276
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Da: Outer Print, Richmond, VA, U.S.A.
Hardcover. Condizione: Near Fine. 2nd Edition. Near Fine hardcover in illustrated boards. Clean and bright with no signs of wear or aging. 274 pp. Codice articolo 005796
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Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Germania
Gebunden. Condizione: Sehr gut. Gebraucht - Sehr gut Leichte Lagerspuren -Like its widely praised, best-selling predecessor, this second edition explains how to use linear models in physical science, engineering, social science, and business applications. The material on interpreting linear models now distinguishes the main applications of prediction and explanation and introduces elementary notions of causality. This edition also covers QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates. It extensively uses R's ggplot2 graphics package in addition to base graphics. 286 pp. Englisch. Codice articolo INF1001460924
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