Unfortunately, the result is not very satisfactory: By default it will tell you the percentage of observations that fall in each category. The graph bar command tell Stata you want to make a bar graph, and the over() option tells it which variable defines the categories to be described. Begin with the sat variable (job satisfaction) and the most basic bar graph: The most basic task of a bar graph is to help you understand the distribution of a single categorical variable.

female: a binary variable which is 1 if the respondent is female and 0 if the respondent is male.It is 0 if the respondent said they were likely to leave and 1 otherwise. stay: a binary variable based on leave.leave: responses to the question 'How likely are you to leave your job in the next year?' on a five-point scale ranging from 'Very Likely' to 'Very Unlikely.'.eng: a numeric measure of employee engagement from 1 to 100.sat: responses to the question 'In general, how satisfied are you with your job?' on a five-point scale ranging from 'Very Dissatisfied' to 'Very Satisfied.'.It contains fictional data with 1,000 observations and four variables: You can obtain the data by typing, or more likely copying and pasting, the following in a do file: SSCC's statistical consultants have been asked to analyze several workplace surveys in recent years, so the example data we'll use has that theme (much of this article came out of our efforts to find ways to present our results to very busy leaders). This article will show you how to make a variety of useful bar graphs using Stata. They can be understood at a glance by both technical and non-technical audiences, and often tell you much more than summary statistics will. Bar graphs are simple but powerful (or rather, powerful because they are simple) tools for conveying information.

Stata 13 for dummies