5 Table 11 11 show's a SAS printout from fitting the multiple regression model to the data hom Table 9.1. excluding D.C., on Y = violent crime rate. X = poverty rate. and X2 = pescent living in metropolitan areas TABLE 11.11 Sum of Mean Source DF Squares Model 2 2448368.07 Square 1224184.04 F Value 31.249 Prob>F 0.0001 Error Total 47 1841257.15 49 4289625.22 39175.68 Root MSE 197.928 R-square 0.5708 Standard Parameter Standard T for HQ: -ized Variable Estimate Error Parameter=0 Prob T Estimate INTERCEP -498.683 140.988 -3.537 0.0009 0.000 POVERTY 32.622 6.677 4.885 0.0001 0.473 METRO 9.112 1.321 6.900 0.0001 0.668 Pearson Correlation Coefficients VIOLENT POVERTY METRO VIOLENT 1.00000 0.36875 0.59396 POVERTY METRO 0.36875 0.59396 1.00000 -0.15562 -0.15562 1.00000

a) Report the prediction equation. and interpret the estimated regression coefficients

b) Find the predicted violent crime sate for Massachusetts. Find the residual. and inter- pret

c) Interpret the fit by showing the prediction equation relating Y and X, for states with (i X = 0. (ii) X = 50. (iii) X = 100. Interpre

d) Interpret the correlation matrix.

e) Report R and the multiple conelation, and interpret

f) Find the parual correlation between violent crime rate and poverty, controlling for metro- politan rate. Interpret g) Refer to

(f) Interpret the squared partial correlation.

h) Show how to construct the F statistic for testing Hu B = B = 0. report its df values and P-value, and interpret i) Show how to construct the statistic for testing Ho. B = 0. report its df and its P-value for H: B10. and interpret. j) Construct a 95% confidence interval for 81, and interpret.