Graphics for statistics and data analysis with R:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton ; London ; New York
CRC Press
[2018]
|
| Edition: | Second edition |
| Series: | Chapman & Hall/CRC texts in statistical science series
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xx, 590 Seiten Illustrationen, Diagramme (teilweise farbig) |
| ISBN: | 9781498779838 |
Staff View
MARC
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Record in the Search Index
| _version_ | 1804178599781072896 |
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| adam_text | Contents
Preface to the First Edition xv
Preface to the Second Edition xvii
Acknowledgments xix
I Introduction 1
1 The Graphical Display of Information 3
1.1 Introduction 3
1.2 Learning Outcomes 7
1.3 Know the Intended Audience 7
1.4 Principles of Effective Statistical Graphs 9
1.4.1 The Layout of a Graphical Display 9
1.4.2 The Design of Graphical Displays 11
1.5 Graphicacy 13
1.6 The Grammar of Graphics 18
1.7 Graphical Statistics 24
1.8 Conclusion 26
1.9 Exercises 26
II A Single Discrete Variable 31
2 Basic Charts for the Distribution of a Single Discrete
Variable 33
33
2.1 Introduction
VI
CONTENTS
2.2 Learning Outcomes 34
2.3 An Example from the United Nations 35
2.4 The Dot Chart 36
2.5 The Bar Chart 44
2.5.1 Definition 44
2.5.2 Pseudo-Three-Dimensional Bar Chart 57
2.6 The Pie Chart 58
2.6.1 Definition 58
2.6.2 Pseudo-Three-Dimensional Pie Chart 61
2.6.3 Recommendations Concerning the Pie Chart 65
2.7 Conclusion 66
2.8 Exercises 68
3 Advanced Charts for the Distribution of a Single Discrete
Variable 75
3.1 Introduction 75
3.2 Learning Outcomes 76
3.3 The Stacked Bar Chart 76
3.3.1 Definition 76
3.3.2 The Stacked Bar Plot versus the Bar Chart and the Pie
Chart 81
3.4 The Pictograph 83
3.4.1 Definition 83
3.4.2 The Pictograph versus the Dot Chart and the Bar
Chart 87
3.5 Variations on the Dot and Bar Charts 91
3.5.1 The Bar-Whisker Chart 92
3.5.2 Dot-Whisker Chart 96
3.6 Frames, Grid Lines, and Order 100
3.6.1 Frame 101
3.6.2 Grid Lines 102
3.6.3 Order 103
CONTENTS vii
3.7 Conclusion 104
3.8 Exercises 105
III A Single Continuous Variable 109
4 Exploratory Plots for the Distribution of a Single
Continuous Variable 111
4.1 Introduction 111
4.2 Learning Outcomes 111
4.3 The Dotplot 112
4.3.1 Definition 112
4.3.2 Variations on the Dotplot 113
4.4 The Stemplot 116
4.4.1 Definition 116
4.5 The Boxplot 124
4.5.1 Definition 124
4.5.2 Variations on the Boxplot 127
4.6 The EDF Plot 133
4.6.1 Definition 133
4.6.2 The EDF Plot as a Diagnostic Tool 140
4.7 Conclusion 142
4.8 Exercises 142
5 Diagnostic Plots for the Distribution of a Continuous
Variable 147
5.1 Introduction 147
5.2 Learning Outcomes 147
5.3 The Quantile-Quantile Plot 148
5.4 The Probability Plot 157
5.5 Estimation of Quartiles and Percentiles* 158
5.5.1 Estimation of Quartiles 159
5.5.2 Estimation of Percentiles
165
vni
5.6 Conclusion
5.7 Exercises
CONTENTS
173
173
6 Nonparametric Density Estimation for a Single Continuous
Variable 177
6.1 Introduction 177
6.2 Learning Outcomes 177
6.3 The Histogram 178
6.3.1 Definition 178
6.3.2 A Circular Variation on the Histogram: The Rose
Diagram 193
6.4 Kernel Density Estimation* 195
6.5 Spline Density Estimation* 224
6.6 Choosing a Plot for a Continuous Variable* 224
6.7 Conclusion 231
6.8 Exercises 235
7 Parametric Density Estimation for a Single Continuous
Variable 239
7.1 Introduction 239
7.2 Learning Outcomes 240
7.3 Normal Density Estimation 241
7.4 Transformations to Normality 246
7.5 Pearson’s Curves* 251
7.6 Gram-Charlier Series Expansion* 260
7.7 Conclusion 263
7.8 Exercises 266
IV Two Variables 273
8 Depicting the Distribution of Two Discrete Variables 275
8.1 Introduction 275
8.2 Learning Outcomes 275
CONTENTS
IX
8.3 The Grouped Dot Chart 276
8.4 The Grouped Dot-Whisker Chart 284
8.5 The Two-Way Dot Chart 289
8.6 The Multi-Valued Dot Chart 294
8.7 The Side-by-Side Bar Chart 295
8.8 The Side-by-Side Bar-Whisker Chart 295
8.9 The Side-by-Side Stacked Bar Chart 297
8.10 The Side-by-Side Pie Chart 300
8.11 The Mosaic Chart 303
8.12 Conclusion 311
8.13 Exercises 313
Depicting the Distribution of One Continuous Variable and
One Discrete Variable 317
9.1 Introduction 317
9.2 Learning Outcomes 317
9.3 The Side-by-Side Dotplot 318
9.4 The Side-by-Side Boxplot 321
9.5 The Notched Boxplot 324
9.6 The Variable-Width Boxplot 327
9.7 The Back-to-Back Stemplot 332
9.8 The Side-by-Side Stemplot 333
9.9 The Side-by-Side Dot-Whisker Plot 333
9.10 The Trellis Kernel Density Estimate* 340
9.11 Conclusion 344
9.12 Exercises 345
10 Depicting the Distribution of Two Continuous Variables 349
10.1 Introduction 349
10.2 Learning Outcomes 349
10.3 The Scatterplot 350
10.4 The Sunflower Plot
353
CONTENTS
10.5 The Bagplot 357
10.6 The Two-Dimensional Histogram 362
10.6.1 Definition 362
10.6.2 The Levelplot 365
10.6.3 The Cloud Plot 370
10.7 Two-Dimensional Kernel Density Estimation* 373
10.7.1 Definition 373
10.7.2 The Contour Plot 378
10.7.3 The Wireframe Plot 381
10.8 Conclusion 384
10.9 Exercises 386
V Statistical Models for Two or More Variables 393
11 Simple Linear Regression: Graphical Displays 395
11.1 Introduction 395
11.2 Learning Outcomes 399
11.3 The Simple Linear Regression Model 400
11.3.1 Definition 400
11.3.2 The Scatterplot 400
11.3.3 The Sunflower Plot 403
11.4 Residual Analysis 414
11.4.1 Definition 414
11.4.2 Residual Scatterplots 414
11.4.3 Depicting the Distribution of the Residuals 419
11.4.4 Depicting the Distribution of the Semistandardized
Residuals 420
11.5 Influence Analysis 420
11.5.1 Definition 420
11.5.2 Matrix Notation for the Simple Linear Regression
Model
422
CONTENTS xi
11.5.3 Depicting Standardized Residuals 423
11.5.4 Depicting the Distribution of Studentized Residuals 424
11.5.5 Depicting Leverage 427
11.5.6 Depicting DFFITS 428
11.5.7 Depicting DFBETAS 430
11.5.8 Depicting Cook’s Distance 432
11.5.9 Influence Plots 433
11.6 Conclusion 435
11.7 Exercises 438
12 Polynomial Regression and Data Smoothing: Graphical
Displays 441
12.1 Introduction 441
12.2 Learning Outcomes 443
12.3 The Polynomial Regression Model 443
12.4 Splines 447
12.5 Locally Weighted Polynomial Regression 453
12.6 Conclusion 464
12.7 Exercises 464
13 Visualizing Multivariate Data 469
13.1 Introduction 469
13.2 Learning Outcomes 469
13.3 Depicting Distributions of Three or More Discrete Variables 470
13.3.1 The Sinking of the Titanic 470
13.3.2 Thermometer Chart 472
13.3.3 Three-Dimensional Bar Chart 475
13.3.4 Trellis Three-Dimensional Bar Chart 476
13.4 Depicting Distributions of One Discrete Variable and Two or
More Continuous Variables 480
13.4.1 Anderson’s Iris Data 480
13.4.2 The Superposed Scatterplot 481
CONTENTS
13.4.3 The Superposed Three-Dimensional Scatterplot 483
13.4.4 The Scatterplot Matrix 487
13.4.5 The Parallel Coordinates Plot 490
13.4.6 The Trellis Plot 491
13.5 Observations of Multiple Variables 495
13.5.1 OECD Healthcare Service Data 495
13.5.2 Chernoff’s Faces 497
13.5.3 The Star Plot 501
13.5.4 The Rose Plot 504
13.6 The Multiple Linear Regression Model 505
13.6.1 Definition 505
13.6.2 Modeling Perch Mass 507
13.6.3 Residual Scatterplot Matrix 508
13.6.4 Leverage Scatterplot Matrix 511
13.6.5 Influence Plot 513
13.6.6 Partial-Regression Scatterplot Matrix 513
13.6.7 Partial-Residual Scatterplot Matrix 515
13.6.8 Summary of the Model for Perch Mass 518
13.7 Conclusion 518
13.8 Exercises 519
VI Appendices 523
A Human Visualization 525
A.l Introduction 525
A.2 Learning Outcomes 525
A.3 Optics 526
A.3.1 Introduction 526
A.3.2 Geometrical Optics 527
A.3.3 The Light Spectrum 529
A.4 Anatomy of the Human Eye 529
CONTENTS xiii
A.5 The Perception of Color 534
A.6 Graphical Perception 545
A.6.1 Weber’s Law 545
A.6.2 Stevens’s Law 548
A.6.3 The Gestalt Laws of Organization 550
A.6.4 Kosslyn’s Image Processing Model 551
A.7 Conclusion 551
A. 8 Exercises 552
B Color Rendering 555
B. l Introduction 555
B.2 Learning Outcomes 555
B.3 RGB and XYZ Color Spaces 556
B.4 HSL and HSV Color Spaces 561
B.5 CIELAB and CIELUV Color Spaces 562
B.6 HCL Color Space 563
B.7 CMYK Color Space 564
B.8 Displaying Color in R 566
B.9 Saving Color Documents from R 569
B.10 Conclusion 571
B.ll Exercises 572
Bibliography 575
Index
585
|
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| indexdate | 2024-07-10T08:06:32Z |
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| language | English |
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| spelling | Keen, Kevin J. Verfasser (DE-588)1022354523 aut Graphics for statistics and data analysis with R Kevin J. Keen Second edition Boca Raton ; London ; New York CRC Press [2018] © 2018 xx, 590 Seiten Illustrationen, Diagramme (teilweise farbig) txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC texts in statistical science series Datenanalyse (DE-588)4123037-1 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Grafische Darstellung (DE-588)4129552-3 gnd rswk-swf Visualisierung (DE-588)4188417-6 gnd rswk-swf Datenanalyse (DE-588)4123037-1 s Grafische Darstellung (DE-588)4129552-3 s Visualisierung (DE-588)4188417-6 s R Programm (DE-588)4705956-4 s DE-604 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030389744&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Keen, Kevin J. Graphics for statistics and data analysis with R Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd Grafische Darstellung (DE-588)4129552-3 gnd Visualisierung (DE-588)4188417-6 gnd |
| subject_GND | (DE-588)4123037-1 (DE-588)4705956-4 (DE-588)4129552-3 (DE-588)4188417-6 |
| title | Graphics for statistics and data analysis with R |
| title_auth | Graphics for statistics and data analysis with R |
| title_exact_search | Graphics for statistics and data analysis with R |
| title_full | Graphics for statistics and data analysis with R Kevin J. Keen |
| title_fullStr | Graphics for statistics and data analysis with R Kevin J. Keen |
| title_full_unstemmed | Graphics for statistics and data analysis with R Kevin J. Keen |
| title_short | Graphics for statistics and data analysis with R |
| title_sort | graphics for statistics and data analysis with r |
| topic | Datenanalyse (DE-588)4123037-1 gnd R Programm (DE-588)4705956-4 gnd Grafische Darstellung (DE-588)4129552-3 gnd Visualisierung (DE-588)4188417-6 gnd |
| topic_facet | Datenanalyse R Programm Grafische Darstellung Visualisierung |
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