In our case, we are only plotting variable earnings, which is by definition the first variable we are plotting, therefore all sub-options refer to 1: bar(1, fcolor(dkgreen)). Remember that we need to specify this option for each variable we are plotting in the bars. Remember that relabelling follows the order in which the values appear: e.g., for treated and untreated, the not treated group appears first and the treated group appears second, therefore we have to use 1 to indicate the non-treated group and 2 to indicate the treated group: over(treated, relabel(1 'Not treated' 2 'Treated')) - the background color is white: we do this with the option graphregion(color()) - the color of the bars is dark green: we do this using the option bar and its suboptions. For example, let’s modify our latest bar graph such that: - the title is “Earnings by region and treatment”: we do this with the option title() - the axis title is “Earnings (average)”: we do this with the option ytitle() - the regions and the treatment status are labeled: we do this with the sub-option relabel within the over option, over(varname, relabel()). Let’s see how to add some of these customizations to our graphs in practice. Namely, we can include and adjust the following: In order to customize our graph further, we can use the tools in the Stata graph window or the graph option commands we have been using in this module. svg files cannot be used with LaTeX PDF output. This may be particularly helpful if you plan to use LaTeX for writing your paper, as. However, you should keep in mind that you can also export graphs in other formats such as. So far, we have been exporting our graphs in svg format. This plot works well when we are interested in showing relationships and groupings among variables from relatively large data sets. Scatter plots are frequently used to demonstrate how two quantitative variables are related to one another. Try to answer these questions: Who is our audience? What is the question you’re trying to answer? 9.1 Types of graphs 9.1.1 Scatter plot Before creating any graphs, be sure to identify the message you want the graph to convey.

Instead, the challenge is figuring out which graph will do the best job at telling your empirical story. The real challenge is not understanding how to use Stata to create graphs. It can be a powerful medium to motivate your research, illustrate relationships between variables and provide some intuition behind why you applied certain econometric methods. Data visualization is an effective way of communicating ideas to your audience, whether it’s for an academic paper or a business setting.

Xline stata title