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• Introduction
• Why graphs are an important tool for exploratory data analysis
• Data management tools for graphing data
• The example dataset
• How to create and edit basic graphs using Stata
• How to create and edit graphs with dialog boxes
• How to edit graphs with the Graph Editor
• How to create and edit graphs with commands
• Some basic graphs
• Graphs for one continuous variable
• Graphs for one categorical variable
• Graphs for two continuous variables
• Graphs for two categorical variables
• Graphs for one continuous and one categorical variable
• Graphs for many variables
• Storing, saving, and exporting graphs
• Storing graphs in memory
• Saving graphs to disk
• Exporting graphs in .png format
• Automating the process: Looping and saving

• Introduction
• Model checking using graphs
• Using the predict command
• Checking model assumptions
• Checking the normality assumption
• Checking the linearity assumption
• Checking the homoskedasticity assumption
• Identifying outliers and influential observations
• Visualizing the results of your models
• Using the margins and marginsplot commands
• A brief review of factor variables
• Categorical independent variables
• Multiple categorical independent variables
• Continuous independent variables
• Continuous and categorical independent variables
• Average response versus response at average: The atmeans option
• Contrasts of margins
• Marginal effects: Margins of derivatives of responses
• Using contour plots to visualize continuous-by-continuous interactions

• Introduction
• Formatting titles, legends, and text boxes
• Formatting titles
• Formatting legends
• Adding text boxes
• Using italics, bold, superscripts, and subscripts
• Using specialty characters
• Using different fonts
• Formatting numbers
• Formatting axes, axis labels, ticks, gridlines, graph, and plot regions
• Formatting categorical axis labels
• Formatting the x and y axes
• Formatting the x- and y-axis labels
• Formatting major and minor ticks and gridlines
• Adding reference lines
• Formatting the graph and plot regions
• Controlling the aspect ratio and size of graphs
• Using schemes to change the overall look of graphs
• Using built-in schemes
• Defining your own schemes
• Recording and saving edits in the Graph Editor

• Introduction
• Layering multiple graphs with the graph twoway command
• Basic layered graphs with one y axis
• Advanced layered graphs with one y axis
• Basic layered graphs with two y axes
• Advanced layered graphs with two y axes
• Layering multiple graphs with the addplot() option
• Basic
• Advanced
• Creating multiple graphs with the by() option
• Combining different graphs with the graph combine command
• Basics: Making a table of separate graphs
• Advanced: Making a single complex graph from separate graphs
• Exporting graphs for publication
• Exporting graphs in pixel-based formats
• Exporting graphs in vector-based formats

Note: The previous four lessons constitute the core material of the course. The following material is optional and introduces community-contributed graphic commands and useful data management tools.

• Introduction
• Community-contributed graph commands
• The Statistical Software Components (SSC) archive
• The coefplot package by Ben Jann
• How to write a simple graphics wrapper command
• How to create animated graphs
• Some fun graphs
• How to create normal curves with shaded tails
• How to show scatterplots with regression lines and residuals
• How to add normal curves to regression lines
• How to graph a histogram with a box plot

Appendix: Data management tools useful for graphing data

• The destring and encode commands
• The recode command
• The tabulate command with the generate() option
• The egen command
• The contract and collapse commands
• The statsby command
• The snapshot command
• The reshape command
• Macros and loops
• Extracting value labels to local macros