The information provided indicates that the means test is too narrow because it excludes factors like the type of engineer, amount of education, and experience. The type of engineer or educational level may be a reflection of the gender with lower earnings.
Additional information on the factors, including gender, education, and the type of engineer, could enhance the research.
Then, it is advised to build a multiple regression where the wage is the dependent variable and the other four variables are independent variables. The "difference in means" test is not appropriate for identifying gender bias in salary setting due to the significance of the omitted variable.
The variables which are likely useful to add to the regression to control for important omitted variables are excessive drug or alcohol use and their gang activity.
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