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| 文件名: A Handbook of Statistical Analyses Using R.pdf | |
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Contents
List of Tables xv List of Figures xvii Preface xxiii I Introduction to Data Science 1 1 Prologue: Why data science? 3 1.1 What is data science? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Case study: The evolution of sabermetrics . . . . . . . . . . . . . . . . . . 6 1.3 Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Further resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Data visualization 9 2.1 The 2012 federal election cycle . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Are these two groups different? .......................................................................10 2.1.2 Graphing variation ....................................................................................... 11 2.1.3 Examining relationships among variables ................................................... 12 2.1.4 Networks .............................................................................................................13 2.2 Composing data graphics ........................................................................................ 14 2.2.1 A taxonomy for data graphics ................................................................ 14 2.2.2 Color ............................................................................................................. 19 2.2.3 Dissecting data graphics .............................................................................. 20 2.3 Importance of data graphics: Challenger .............................................................. 23 2.4 Creating effective presentations............................................................................. 27 2.5 The wider world of data visualization .................................................................... 28 2.6 Further resources ........................................................................................................... 30 2.7 Exercises .................................................................................................................. 30 3 A grammar for graphics 33 3.1 A grammar for data graphics ............................................................................ 33 3.1.1 Aesthetics ..................................................................................................... 34 3.1.2 Scale ............................................................................................................. 37 3.1.3 Guides .......................................................................................................... 38 3.1.4 Facets ........................................................................................................... 38 3.1.5 Layers ........................................................................................................... 38 3.2 Canonical data graphics in R .................................................................................. 39 3.2.1 Univariate displays ....................................................................................... 39 |
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