The result below was obtained by OLS for the model sat = P. + B,hsize + B,hsize2 + B,female + BAblack + B,(female.black There are 4,137 students in the dataset. If the output is not visible on your screen, please click on these links for a copy: linkl , link2 . Two links were provided in case one of them does not work. regress sat hsize hsize2 female black female black Source | SS df MS Number of obs = 4 , 137 F (5, 4131) = 77 . 52 Model | 6894724.95 5 1378944 . 99 Prob > F = 0 . 0000 Residual | 73479121 .4 4 , 131 17787 . 248 R-squared = 0 . 0858 Adj R-squared = 0 . 0847 Total | 80373846.3 4,136 19432. 7481 Root MSE = 133 37sat | Coef. Std. Err. t P>It| [95% Conf. Interval] hsize | 19.29706 3. 832298 5 . 04 0 . 000 11 . 78369 26. 81043 hsize2 | -2. 194828 . 5271635 -4.16 0 . 000 -3 . 228353 -1 . 161304 female | -45 . 09145 4 . 291063 -10 .51 0 . 000 -53 . 50424 -36 . 67866 black | -169 . 8126 12 . 71315 -13 .36 0 . 000 -194 . 7373 -144 . 888 female black | 62 . 30636 18 . 15417 3. 43 0 . 001 26 . 71442 97 . 89829 cons | 1028 . 097 6. 290167 163 . 45 0 . 000 1015 .765 1040 . 429estat imtest, white White's test HO: Homoskedasticity Ha: Unrestricted heteroskedasticity chi2 (13) = 39. 09 Prob > chi2 = 0. 0002 Cameron & Trivedi's decomposition of IM-test Source | chi2 df P Heteroskedasticity | 39 . 09 13 0 . 0002 Skewness | 17 .21 5 0 . 0041 Kurtosis | 0. 37 1 0 . 5437 + - - Total | 56 . 67 19 0 . 0000 vii. What are the potential consequences of heteroskedasticity for OLS