# Interaction of Gender and Income categorical variable

I ran the following model, with exam scores in science as my outcome variable, and parental income group divided into 5 groups and a binary gender variable with the results below:

regress test_score i.quantiles_parent_income i.gender_dummy

Source |       SS           df       MS      Number of obs   =     2,268
-------------+----------------------------------   F(6, 2261)      =    318.19
Model |  76430.8521         6  12738.4753   Prob > F        =    0.0000
Residual |    90516.86     2,261  40.0339938   R-squared       =    0.4578
-------------+----------------------------------   Adj R-squared   =    0.4564
Total |  166947.712     2,267  73.6425726   Root MSE        =    6.3272

--------------------------------------------------------------------------------------------
test_score |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
quantiles_parent_income|
2  |  -.9545663   .5365921    -1.78   0.075    -2.006831    .0976982
3  |   .0265901   .5395947     0.05   0.961    -1.031563    1.084743
4  |   5.121439   .5328825     9.61   0.000      4.07645    6.166429
5  |   7.491982   .5170866    14.49   0.000     6.477968    8.505996
|
gender_dummy |
male  |  -8.225431   .2901021   -28.35   0.000    -8.794325   -7.656537

I then ran an F-test between students whose parents fall in the 2nd quantile, relative to the top 20th percentile:

test i2.quantiles_parent_income== i5.quantiles_parent_income
F(  1,  2261) =  415.54
Prob > F =    0.0000

Can I say that a student living in the top 20th percentile scores on average, 7.5 points higher than a student in 2nd quantile, and the result is significant at the 99 significance level. Is it possible to compute how being a male in the top 20th percentile impacts one's test scores in science compared to a female student in the same parental income group?