1. Use the outputs below to answer each of the following questions. Dummy = 1 if the resume has a white-sounding name. gen white=(race=="b") Dummy =1 if the sex listed in the resume is male. gen male=(sex=="m") Interaction of male and white-sounding name. gen malexwhite-male*white- reg call white male malexwhite yearsexp honors black Source SS df MS Number of obs = F(5, 4864) 4,870 = 11.27 Model Residual 4.12910997 356.317707 5 .825821994 4,864 .073256108 Prob > F R-squared = 0.0000 = 0.0115 Adj R-squared = 0.0104 Total 360.446817 4,869 .074028921 Root MSE = .27066 call Coef. Std. Err. t P>|t| [95% Conf. Interval] black white male -.0328219 -.0090218 malexwhite .0044081 .0088447 .0129162 .0184171 yearsexp .0028339 .000776 honors .0784413 .0175035 _ cons .0721238 .008744 -3.71 0.000 -0.70 0.485 0.24 0.811 3.65 0.000 4.48 0.000 8.25 0.000 -.0501615 -.0154823 -.0343434 .0162997 -.0316978 .040514 .0013125 0043552 .0441265 .112756 0549816 .0892661 test white malexwhite=0 black (1) white malexwhite = 0 (2) white = 0 F 2, 4864) = Prob F = reg call white male 8.43 0.0002 malexwhite yearsexp honors, level (90) Source SS df MS Number of obs F(5, 4864) = 4,870 = 11.27 Model Residual 4.12910997 356.317707 4,864 5 .825821994 073256108 Prob > F R-squared = 0.0000 = 0.0115 Total 360.446817 4,869 .074028921 Adj R-squared Root MSE = 0.0104 = .27066 call Coef. Std. Err. t P>|t| [90% Conf. Interval] white male malexwhite yearsexp honors _cons -.0328219 0088447 -.0090218 .0129162 .0044081 0184171 0028339 .000776 .0784413 .0175035 .0721238 -3.71 0.000 -0.70 0.485 -.0473729 -.0182709 -.0302711 .0122274 0.24 0.811 -.0258912 .0347073 3.65 0.000 .0015572 .0041105 4.48 0.000 .0496451 .1072374 .008744 8.25 0.000 .0577384 .0865092 display invttail ( 4864 ' .05/2) 1.9604518