Graphs Everyone Should Know and How to Create Them in Stata

Franz 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.

Table of Contents:
I Graphs for univariate data Histograms Introduction A basic histogram Spike plots Histograms with varying bin widths Multiple histograms Mirrored histograms Ridgeline histograms Kernel density plots Introduction A basic kernel density plot Cumulative distribution plots Multiple kernel density plots Mirrored kernel density plots Ridgeline kernel density plots Box plots Introduction A basic box plot Horizontal box plots Box plots with histograms Multiple box plots Violin plots Introduction A basic violin plot Horizontal violin plots Multiple violin plots Custom widths Dot plots Introduction A basic dot plot Multiple dot plots Horizontal dot plots Beam plots Dot plots with box plots Cumulative dot plots Stem-and-leaf plots Introduction A basic stem-and-leaf plot A graphical stem-and-leaf plot A horizontal stem-and-leaf plot Mirrored stem-and-leaf plots Distributional diagnostic plots Introduction Symmetry plots Skew plots Quantile-uniform plots Quantile-normal plots Quantile χ plots Quantile–quantile plots Rootograms Introduction A basic rootogram Hanging rootograms Univariate bar charts Introduction A basic frequency bar chart Percentage bar charts Horizontal bar charts Sorted bar charts Multiple bar charts Dot charts Pie charts Introduction A basic pie chart Multiple pie charts Radar charts Introduction A basic radar chart Multiple-radar charts Radar charts with too few or too many categories Frequency radar chart II Graphs for bivariate data Scatterplots Introduction A basic scatterplot Scatterplots with multiple y and x variables Scatterplots over categorical groups Scatterplots with marginal distributions Binned scatterplots Heat plots Introduction A basic heat plot Hex-heat plots Sunflower plots Line plots Introduction A basic area plot Sparkline plots Area and shaded range plots Introduction A basic area plot Data with variation Shaded range plots Pair plots Multiple area and shaded range plots Lines of best fit Introduction A basic best fit plot Quadratic fits Fractional polynomial fits Multiple lines of best fit Custom polynomial fits Multiple custom polynomial fits Constrained lines of best fit Nonparametric fits (smoothers) Lines of best fit with confidence intervals Multiple lines of best fit with confidence intervals Lines of best fit with recast confidence intervals Jitter plots Introduction A basic jitter plot A complex jitter plot Jitter plots with continuous values Table plots Introduction A basic table plot Three-way table plot Balloon plots Bivariate bar charts Introduction A basic two-way frequency bar chart Stacked bar charts Introduction A basic two-way stacked frequency bar chart Two-way stacked percentage bar chart Slide plots Mosaic plots III Graphs for multivariate data Matrix plots Introduction Correlation matrix Matrix scatterplots Cross plots Trellis plots Contour plots Introduction A basic contour plot Contour-line plots Contour plots with custom colors Contour plots with small and incomplete datasets Trivariate heat plots Introduction A basic trivariate heat plot Bubble plots Introduction A basic bubble plot Chernoff faces Introduction Basic Chernoff faces Triplots Introduction A basic triplot 3D scatterplot Introduction A basic 3D scatterplot 3D scatterplot without autoscaling 3D surface plots IV Special graphs Animated graphs Introduction A basic animated graph Rainbow plots Introduction A basic rainbow plot A complex rainbow line plot A complex rainbow box plot Plotting regression results Introduction Visualizing coefficients from one regression Plotting coefficients from two regressions Plotting coefficients from four regressions Plotting coefficients from a regression with an interaction term Maps Introduction A basic geographic map Choropleth maps Submaps Plotting equations Introduction A basic mathematical function A custom equation A statistical function Polynomial regression terms References Author index Subject index

About the Author :
Franz Buscha is a Professor of Economics in the School of Organisations, Economy and Society at the University of Westminster (London, U.K.) with 20 years of Stata and econometric experience. Franz's research specializes in areas of labour economics, including the 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.