Question

The following output is regression of hourly EARNINGS ON HEIGHT a. Create a 99% confidence interval for the slope coufficient and interpretit D. is the slope cofficient on HEIGHT statistically significant at a level of significance of 197. Years of schooling Salso acts EARNINGS but has not been added to the regression. Where does the effect of Soccur in this regression output? SUMMARY OUTPUT Regression Statistics Multiple R 0.241124399 R Square 0.058140976 Adjusted R Square 0.056390309 Standard Error 15.96556082 Observations 540 ANOVA df Significance F 1.3936E-08 1 Regression Residual Total 538 539 SS MS 8465.391478 8465.391 33.21075 137135.7332 254.8991 145601.1246 Intercept HEIGHT Coefficients Standard Error t Stat P-value Lower 95% Upper 95% -43.5705454 11.04088217 -3.94629 8.99E-05 -65.25906861 -21.882 0.939973809 0.16310843 5.762877 1.39E-08 0.619566353 1.260381 A 1.99% confidence interval is 0.52 <B1 < 1.38.b. No. 51 = 0 is key. We tal to reject He: B1-6. c. Efect of on eamings appears in the SSE (sum of soured residus) because it affects EARNINGS but has not been added as an exploratory variable in the regression B. 100% confidence interval is 0.82 < PI<1.36.B. Yes, it is notky to be 0. We reject Hot B1-0 and accept H1:1 is not ... Efect of Son earnings appears in the SSE (sum of squared residuale because aftects EARNINGS but has not been added as an exploratory variable in the region 2.99% corridence interval is 0.2 <P! < 1.26.b. Yes, is not likely to be 0. We reject Ho: 1-O and accept 1:1 is not 0.6. Effect of on earnings appears in the SSE (sumo quared residually because affects EARNINGS but has not been added as an exploratory variable in the region 99% confidence interval is 0.52 <1 1.38.b. Yes is not in the confidence interval is not to be. We reject 10 and accept 1:1 is not 0.c. Efectos on earingspears in the Regression sum of squares the variation in earnings that was explained by the regression because it affects EARNINGS but has not been added as an explanatory variable in the regression

Answer 1

tells confidence internal: 2 = 0.01 = 2.617 t2 = 0.01,538 C.I P[ & , - 2.617 se (f) = 8,5 8 +2617 seqßs] c. I=P[0.94 - 2.62 (0.16) CBS 0.94+2.62 (0.10] C.I - P[ 0.52 LBL 1.36] The confidence internal that if we take 100 such interuals then 99 of the internal will contain true ß. b) Ho Bizo Hi! B, 20 Using the obtained in las me te rejet hypother, enis at lend of significan the value of Bi lies in the confidence Internal Therepe. Height day is not significant, e) This will result in highe value of. Residual sum of squares the CI the rule as The correct answer in Option B