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ggplot2 extended
Welcome
Preface
Introduction
Basics
1
ggplot2
Layers
2
Data
3
Geoms
4
Stats
5
Annotations
6
Scales and guides
7
Coords
8
Facets
9
Themes
Special cases
10
Maps
11
Networks
12
Interactive plots
13
Animated plots
Shortcuts
14
Helpers
15
Interactive tools
Getting ready to publish
16
Finishing touches
17
Arranging plots
Beyond R
18
Python
Case studies
References
Table of contents
4.1
Combining data visualization and statistical modeling
4.2
Convex hull
4.3
Inferential statistical tests
4.3.1
F-test
4.3.2
Pearson’s Chi-squared test
4.3.3
Test for association between paired samples
4.3.4
Test of equal or given proportions
4.3.5
T-test
4.4
Interaction plot
4.4.1
CGPfunctions
4.5
Linear regression
4.5.1
Diagnostic plots
4.5.2
Regression line equation and R-square
4.6
Lorenz Curve
4.7
Markov chain Monte Carlo
4.8
Multi-stat binning layer
4.9
Overlay normal density plot
4.10
P-values
4.11
P-P plot
4.12
Q-Q plot
4.13
Quality control chart
4.14
Proportions according to custom denominator
4.15
Random rorests
4.16
ROC curves
4.17
Sample data and distribution vectors
4.18
Seasonal adjustment
4.19
Statistics for reporting the results of model fits
4.20
Survival analysis
4.21
Tornado plot
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4.1
Combining data visualization and statistical modeling
4.2
Convex hull
4.3
Inferential statistical tests
4.3.1
F-test
4.3.2
Pearson’s Chi-squared test
4.3.3
Test for association between paired samples
4.3.4
Test of equal or given proportions
4.3.5
T-test
4.4
Interaction plot
4.4.1
CGPfunctions
4.5
Linear regression
4.5.1
Diagnostic plots
4.5.2
Regression line equation and R-square
4.6
Lorenz Curve
4.7
Markov chain Monte Carlo
4.8
Multi-stat binning layer
4.9
Overlay normal density plot
4.10
P-values
4.11
P-P plot
4.12
Q-Q plot
4.13
Quality control chart
4.14
Proportions according to custom denominator
4.15
Random rorests
4.16
ROC curves
4.17
Sample data and distribution vectors
4.18
Seasonal adjustment
4.19
Statistics for reporting the results of model fits
4.20
Survival analysis
4.21
Tornado plot
3
Geoms
5
Annotations