reg wage educ Source SS df MS Number of obs 300 F (1, 298) 56.83 Model 44521627.2 1 44521627.2 Prob > F 0.0000 Residual 233438930 298 783352.115 R-squared 0.1602 Adj R-squared II 0.1574 Total 277960558 299 929633.972 Root MSE 885.07 wage Coefficient Std. err. t p>It| [95% conf. interval] educ 117.1024 15.53312 7.54 0.000 86.53388 147.6709 cons 1256.172 157.9243 7.95 0.000 945.3839 1566.96 reg wage edu , vce(robust) Linear regression Number of obs 300 F(1, 298) 70.91 Prob > F 0.0000 R-squared II 0.1602 Root MSE 885.07 Robust wage Coefficient std. err. t P>It| [95% conf. interval] educ 117.1024 13.9067 8.42 0.000 89.73462 144.4702 _cons 1256.172 151.039 8.32 0.000 958.9339 1553.41g) You are worried whether education will, be rewarded enough in the labor market. You wonder if another year of education will yield an expected $100 more per month. Test the following null hypothesis at the 10% significance level, using both the critical value and the p-value methods: Ho: 1 = 100 vs Hi: B1 # 100. [Calculate this with the formulas we learned in class.] h) The test above is a two-sided test. But, what if your alternative hypothesis was that Hi: B1 > 100? Can you reject the null under this new alternative? Show the answer using both the critical value and the p-value approach