The Global Health Observatory (GHO) keeps tracking the health status in countries for years to find out the predicting factors of the life expectancy (Y) in years. One such important factor is the number of years of schooling (X). The following regression outputs (with some numbers missing) are obtained by fitting a linear regression model for Y on X. SUMMARY OUTPUT Regression Statistics Multiple R 0.81815943 R Square Adj. R Square Standard Error 4.57501316 Observations ANOVA Significance df SS MS F F Regression 1 7246.59454 7246.59454 346.217699 5.92695E-43 Residual 171 3579.15747 20.9307454 Total 172 10825.7520 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept 42.90159072 1.58699604 39.76896535 46.03421609 X 2.228726885 0.11977942 a. Report the fitted equation. b. Interpret the slope estimate. c. Determine the coefficient of determination and discuss its meaning in the context of this problem. d. Determine if there is enough evidence at 5% level to infer that number of years of schooling and life expectancy are linearly related e. Estimate the mean life expectancy of people who attended schools for 12 years with 95% confidence. [Hint: the average number of years of schooling is 12.927, with a sample SD 2.912, for the above 173 countries in the regression outputs.] f. Construct a 95% confidence interval for the life expectancy of a person who attended schools for 12 years