Source MS 526 60.79 0.0000 0.2589 Adj R-squared.2547 3.1884 Number of obs = F(3,

Question

Source MS 526 60.79 0.0000 0.2589 Adj R-squared.2547 3.1884 Number of obs = F(3, 522) df Model 1853.93665 Residual5306.47764 3 617.978884 Prob >F 522 10.165666 R-squared Total 7160.41429 525 13.6388844 Root MSE wage Coef. Std. Err. [95% Conf. Interval] 9.98 0.000 .6847738 2793401 8.14 0.000-2.823452-1.725915 783974 0.95 0.341-. 6882992 1.988011 educ 5053245 .0506227 4058751 female-2.274684 nonwhite.1192245 .4597555 0.26 0.795 -1.022423 cons 6498561 6811618 where wage is monthly wage in USS, educ is years of education, female is a dummy variable which is equal to 1 if the person is female and 0 otherwise, and nonwhite is a dummy variable which is equal to 1 if the person is not White and 0 otherwise

Explanation / Answer

Since the values of both the dmmy variables (Female and Nonwhite) are equal to 1, Regression equation is

Predicted wage = 0.6498561 + 0.5053245 x Years of education - 2.274684 - 0.1192245

= 0.6498561 + (0.5053245 x 6) - 2.274684 - 0.1192245

= - 1.7440524 + 3.031947

= 1.2878946

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