I'm doing a report of the differences between women and men in their performance on a test with variables like: age, education, race and of course genre. I have two options:
doing a linear regression of the performance over age, education and all my variables to check if being a women makes an statistically significant difference.
Presenting exhausting descriptive statistics to see the differences between men and women. This descriptive statistics are like some kind of three in which I start by setting groups of age, for each group I separate different levels of education, then for each of those smaller groups I separate race and finally genre. At the end I can do a t test to check if the performance on the test is different for women (compared to men) in each small group.
I'm struggling on deciding how to approach to this problem because:
- I feel that doing the second approach is the same as doing the first one because I feel like "controling" for all variables and then checking if there is a different effect of my variable of interest in each group.
- Nonetheless, my variable of interest can have a different effect in each of the groups as compared with just one possible observable effect with the regression method.
- Besides that, following the second method is easier to explain to the directives. Is easier to say that "white, educated, old women perform better on the test" than "ceteris paribus, women perform better on the test".
What thoughts do you have on my situation?. What would you do and why?. What differences do you find between these approaches?