Consider the regression model WAGE = 1 + 2EDUC + e. WAGE is hourly wage rate in U.S. 2013 dollars. EDUC is years of education attainment, or schooling. The model is estimated using individu- als from an urban area.

WAGE = 10.76 + 2.461965EDUC, N = 986 (se) (2.27) (0.16)

The sample standard deviation of WAGE is 15.96 and the sum of squared residuals from the regres- sion above is 199,705.37. Compute R2.

Using the answer to (a), what is the correlation between WAGE and EDUC? [Hint: What is the

correlation between WAGE and the fitted value WAGE?]

The sample mean and variance of EDUC are 14.315 and 8.555, respectively. Calculate the leverage

of observations with EDUC = 5, 16, and 21. Should any of the values be considered large?

Omitting the ninth observation, a person with 21 years of education and wage rate $30.76, and reestimating the model we find = 14.25 and an estimated slope of 2.470095. Calculate DFBETAS

for this observation. Should it be considered large?

For the ninth observation, used in part (d), DFFITS = 0.0571607. Is this value large? The leverage

value for this observation was found in part (c). How much does the fitted value for this observation

change when this observation is deleted from the sample?

For the ninth observation, used in parts (d) and (e), the least squares residual is 10.18368. Calcu-

late the studentized residual. Should it be considered large?