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week3ans

# week3ans - Week 3 Answers 1 Run a regression of wage on...

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Week 3 Answers 1. Run a regression of wage on education (educ). reg wage educ Source | SS df MS Number of obs = 935 -------------+------------------------------ F( 1, 933) = 111.79 Model | 16340644.5 1 16340644.5 Prob > F = 0.0000 Residual | 136375524 933 146168.836 R-squared = 0.1070 -------------+------------------------------ Adj R-squared = 0.1060 Total | 152716168 934 163507.675 Root MSE = 382.32 ------------------------------------------------------------------------------ wage | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- educ | 60.21428 5.694982 10.57 0.000 49.03783 71.39074 _cons | 146.9524 77.71496 1.89 0.059 -5.56393 299.4688 ------------------------------------------------------------------------------ 2. Interpret the slope and the intercept of the estimated regression line. Slope: A 1 unit increase in education increases the predicted wage by 60.21. Intercept: If education is zero, then the average wage is 146.95. 3. Is the slope coefficient statistically significant? Statistically significant implies that you need to test the following: H 0 : β 1 = 0 H A : β 1 6 = 0 Stata gives the relevant t stat which is 10.57 in this case. At the 5% level of significance, the critical value is 1.96. Thus, | t stat | > 1 . 96, which implies that the null can be rejected. Alternatively, the p-value is 0.000 (also given in the Stata table) which is less than 0.05, therefore, the null can be rejected.

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