Graphs Everyone Should Know and How to Create Them in Stata |
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Comment from the Stata technical groupFranz Buscha's book, Graphs Everyone Should Know and How to Create Them in Stata, is written for anyone who uses Stata to make graphs. Beginners will find a complete collection of tools for effectively visualizing their data and results. Experienced Stata users are certain to learn some new tricks as well. The chapters of the book are organized into four main sections: graphs for univariate data, graphs for bivariate data, graphs for multivariate data, and special graphs. Each chapter introduces a type of graph, explains when and why it is useful for visualizing a particular kind of data, demonstrates how to create that graph using Stata, and shows a few variations. The special graph section covers topics such as how to create maps, plot equations, create animated graphs, and create other specialty graphs. Readers will find it easy to learn to make graphs by example. Buscha demonstrates most graphs using datasets that are installed with your copy of Stata, so it is straightforward to follow along. He also clearly pairs each graph with the command used to create it in a box just above the graph. If you find a graph that you wish to create with your own data, you can take the command from the box and replace the variable names in the example with your own variable names. Buscha's book has two unique features that distinguish it from other books about Stata graphs. First, the book's goal is to clearly demonstrate how to effectively visualize different kinds of data and results from models using only necessary features. It focuses on important options but does not discuss all the options available for customizing each graph. Second, the book introduces many community-contributed graph commands that are freely available and can be downloaded from the internet. Readers may be unaware of these commands before finding them in this book, and they can learn how to use them quickly rather than spend time trying to write custom code for themselves. Graphs Everyone Should Know and How to Create Them in Stata is a reference you will use again and again as you visualize different types of data. You will quickly find the graphs that are applicable to your data and the Stata commands necessary to create them. |
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About the authorFranz Buscha is a professor of economics in the School of Organisations, Economy and Society at the University of Westminster (London, UK) with 20 years of Stata and econometric experience. Franz's research specializes in areas of labor economics, including returns to education and social mobility. He has published in leading journals, contributed to numerous policy reports, and held prestigious grants. He has even had a radio show called Policy Matters for a few years! Franz loves all things Stata and hopes that he will someday be able to learn everything about it. |
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Table of contentsView table of contents >> List of figures
List of tables
Preface (PDF)
Acknowledgments
How to use this book
I Graphs for univariate data
1 Histograms
1.1 Introduction
1.2 A basic histogram
1.2.1 Custom bin widths
1.3 Spike plots 1.2.2 Changing the y axis 1.2.3 Bar labels 1.2.4 Added density plots 1.4 Histograms with varying bin widths 1.5 Multiple histograms 1.6 Mirrored histograms 1.7 Ridgeline histograms 2 Kernel density plots
2.1 Introduction
2.2 A basic kernel density plot
2.2.1 A shaded kernel density plot
2.3 Cumulative distribution plots 2.2.2 Bandwidth choices 2.2.3 Kernel choices 2.4 Multiple kernel density plots 2.5 Mirrored kernel density plots 2.6 Ridgeline kernel density plots 3 Box plots
3.1 Introduction
3.2 A basic box plot
3.2.1 Box plot options
3.3 Horizontal box plots 3.4 Box plots with histograms 3.5 Multiple box plots 4 Violin plots
4.1 Introduction
4.2 A basic violin plot
4.2.1 Custom bandwidths and kernels
4.3 Horizontal violin plots 4.4 Multiple violin plots 4.5 Custom widths 5 Dot plots
5.1 Introduction
5.2 A basic dot plot
5.2.1 Adjusting stack width
5.3 Multiple dot plots 5.2.2 Adjusting marker size 5.2.3 Dot plots without binning 5.4 Horizontal dot plots 5.5 Beam plots 5.6 Dot plots with box plots 5.7 Cumulative dot plots 6 Stem-and-leaf plots
6.1 Introduction
6.2 A basic stem-and-leaf plot
6.2.1 Custom bins
6.3 A graphical stem-and-leaf plot 6.4 A horizontal stem-and-leaf plot 6.5 Mirrored stem-and-leaf plots 7 Distributional diagnostic plots
7.1 Introduction
7.2 Symmetry plots 7.3 Skew plots 7.4 Quantile-uniform plots 7.5 Quantile-normal plots 7.6 Quantile χ plots 7.7 Quantile–quantile plots 8 Rootograms
8.1 Introduction
8.2 A basic rootogram 8.3 Hanging rootograms
8.3.1 Different theoretical distributions
8.3.2 Confidence intervals 9 Univariate bar charts
9.1 Introduction
9.2 A basic frequency bar chart 9.3 Percentage bar charts 9.4 Horizontal bar charts 9.5 Sorted bar charts 9.6 Multiple bar charts 9.7 Dot charts 10 Pie charts
10.1 Introduction
10.2 A basic pie chart
10.2.1 Too many categories
10.3 Multiple pie charts 10.2.2 Labeling pie charts 10.2.3 Exploding pie charts 10.2.4 Sorting pie charts 11 Radar charts
11.1 Introduction
11.2 A basic radar chart
11.2.1 Custom spoke labels
11.3 Multiple-radar charts 11.4 Radar charts with too few or too many categories 11.5 Frequency radar chart II Graphs for bivariate data
12 Scatterplots
12.1 Introduction
12.2 A basic scatterplot
12.2.1 Important marker options
12.3 Scatterplots with multiple y and x variables 12.4 Scatterplots over categorical groups 12.5 Scatterplots with marginal distributions 12.6 Binned scatterplots 13 Heat plots
13.1 Introduction
13.2 A basic heat plot
13.2.1 Heat plot with frequency statistics
13.3 Hex-heat plots 13.2.2 Custom colors 13.2.3 Custom bins 13.2.4 Proportional bin sizes 13.2.5 Scatter heat plots
13.3.1 Custom bins
13.4 Sunflower plots
13.4.1 Custom bins
14 Line plots
14.1 Introduction
14.2 A basic line plot
14.2.1 Important line options
14.3 Sparkline plots 14.2.2 Multiple line plots 14.2.3 Line plots with markers 14.2.4 Different connecting styles 14.2.5 Multiple y axes 14.2.6 Unsorted, sorted, and missing data 14.2.7 Line graphs with arrows
14.3.1 Multiple sparkline plots
15 Area and shaded range plots
15.1 Introduction
15.2 A basic area plot
15.2.1 Different types of area plots
15.3 Data with variation 15.2.2 Important area plot options 15.4 Shaded range plots
15.4.1 Different types of shaded range plots
15.5 Pair plots 15.6 Multiple area and shaded range plots 16 Lines of best fit
16.1 Introduction
16.2 A basic best fit plot
16.2.1 Predicting out of range
16.3 Quadratic fits 16.4 Fractional polynomial fits 16.5 Multiple lines of best fit 16.6 Custom polynomial fits 16.7 Multiple custom polynomial fits 16.8 Custom polynomial fits with functions 16.9 Constrained lines of best fit 16.10 Nonparametric fits (smoothers)
16.10.1 Local polynomial smoother
16.11 Lines of best fit with confidence intervals 16.10.2 Other bivariate smoothers 16.12 Multiple lines of best fit with confidence intervals 16.13 Lines of best fit with recast confidence intervals 17 Jitter plots
17.1 Introduction
17.2 A basic jitter plot 17.3 A complex jitter plot 17.4 Jitter plots with continuous values 18 Table plots
18.1 Introduction
18.2 A basic table plot
18.2.1 Horizontal and percentage table plots
18.3 Three-way table plot 18.2.2 Complex table plot 18.2.3 Framed table plot 18.4 Balloon plots
18.4.1 Custom markers table plots
19 Bivariate bar charts
19.1 Introduction
19.2 A basic two-way frequency bar chart
19.2.1 Horizontal two-way frequency bar chart
19.2.2 Column, row, and cell percentage two-way bar charts 20 Stacked bar charts
20.1 Introduction
20.2 A basic two-way stacked frequency bar chart 20.3 Two-way stacked percentage bar chart 20.4 Slide plots 20.5 Mosaic plots III Graphs for multivariate data
21 Matrix plots
21.1 Introduction
21.2 Correlation matrix 21.3 Matrix scatterplots 21.4 Multiple matrix scatterplots 21.5 Cross plots 21.6 Trellis plots 22 Contour plots
22.1 Introduction
22.2 A basic contour plot
22.2.1 Custom contour levels
22.3 Contour-line plots 22.4 Contour plots with custom colors 22.5 Contour plots with small and incomplete datasets 23 Trivariate heat plots
23.1 Introduction
23.2 A basic trivariate heat plot
23.2.1 Trivariate heat plot with a binary z variable
23.2.2 Trivariate heat plot scaled color fields 23.2.3 Trivariate heat plot with a categorical x variable 23.2.4 Trivariate heat plot with discrete y and x variables 24 Bubble plots
24.1 Introduction
24.2 A basic bubble plot
24.2.1 Bubble plot with marker labels
24.2.2 Bubble plot with different symbols 24.2.3 Bubble plot over multiple groups 25 Chernoff faces
25.1 Introduction
25.2 Basic Chernoff faces
25.2.1 Chernoff faces with custom ordering
25.2.2 Chernoff half faces 26 Triplots
26.1 Introduction
26.2 A basic triplot
26.2.1 Important triplot options
26.2.2 Multiple triplots 27 3D scatterplot
27.1 Introduction
27.2 A basic 3D scatterplot
27.2.1 Rotation
27.3 3D scatterplot without autoscaling 27.2.2 Modifying markers 27.2.3 3D scatterplots over groups 27.3.4 A note on large datasets 27.4 3D surface plots IV Special graphs
28 Animated graphs
28.1 Introduction
28.2 A basic animated graph 29 Rainbow plots
29.1 Introduction
29.2 A basic rainbow plot 29.3 A complex rainbow line plot 29.4 A complex rainbow box plot 30 Plotting regression results
30.1 Introduction
30.2 Visualizing coefficients from one regression
30.2.1 Options for coefplot
30.3 Plotting coefficients from two regressions 30.4 Plotting coefficients from four regressions 30.5 Plotting coefficients from a regression with an interaction term 31 Maps
31.1 Introduction
31.2 A basic geographic map
31.2.1 Custom labels
31.3 Choropleth maps
31.3.1 Customization options
31.4 Submaps 32 Plotting equations
32.1 Introduction
32.2 A basic mathematical function 32.3 A custom equation 32.4 A statistical function
32.4.1 Overlaying
32.5 Polynomial regression terms References
Author index (PDF)
Subject index (PDF)
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