The following is a regression using the same earnings data that we have seen on the...

  

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The following is a regression using the same earnings data that we have seen on the homework. The variable educ represents the number of years of school completed. .reg earnings age educ height weight Source SS df MS Number of obs F(4, 17865) 17,870 911.80 Model 12.1960e+12 Residual | 1.0757e+13 5.4900e+11 17,865 602103714 Prob > F R-squared = 0.0000 Adj R-squared Total 1.2953e+13 17,869 724863544 Root MSE 0.1694 24538 earnings Coefficient Std. err. t P>|t| [95% conf. interval] age educ T 335.571 18.41505 18.22 0.000 299.4757 371.6663 1 3940.177 70.16664 0.000 3802.643 4077.71 height 466.3295 weight -4.977433 3.876278 9.24 0.000 -1.28 367.4161 565.2429 -12.57531 2.620448 cons 3352.679 -15.085 0.000 -57146.16 -44003.01 1 Fill in the blanks Complete the missing information in the Stata output above. 2 SER Calculate the standard error of the regression. Hint: this can be written as S 3 S Calculate the sample variance of earnings. Hint: you could use SER or a sum of squares. The following is a regression using the same earnings data that we have seen on the homework. The variable educ represents the number of years of school completed. .reg earnings age educ height weight Source SS df MS Number of obs F(4, 17865) 17,870 911.80 Model 12.1960e+12 Residual | 1.0757e+13 5.4900e+11 17,865 602103714 Prob > F R-squared = 0.0000 Adj R-squared Total 1.2953e+13 17,869 724863544 Root MSE 0.1694 24538 earnings Coefficient Std. err. t P>|t| [95% conf. interval] age educ T 335.571 18.41505 18.22 0.000 299.4757 371.6663 1 3940.177 70.16664 0.000 3802.643 4077.71 height 466.3295 weight -4.977433 3.876278 9.24 0.000 -1.28 367.4161 565.2429 -12.57531 2.620448 cons 3352.679 -15.085 0.000 -57146.16 -44003.01 1 Fill in the blanks Complete the missing information in the Stata output above. 2 SER Calculate the standard error of the regression. Hint: this can be written as S 3 S Calculate the sample variance of earnings. Hint: you could use SER or a sum of squares.