a) (1 points) Report the least squares prediction equation. b) (1 point) Report the variance of the error term. CHANGE c) (2 points) Estimate the average city mileage for a 360 HP car. d) (2 points) Find R2 for the fitted model. Interpret your result. e) (7 points) Is there sufficient evidence to indicate that this model is useful for predicting CITYMPG of a car? Test using a = 0.01 . List any assumptions that you must make. OHMYTIO pe mua SH 686.58% BOBOS.2486 .2190 .1517 -4.1879 35.00- O Observed O - Quadratic O 30.00- o O DO CITYMPG O 25.00 O oo O OO 20.00- ON 020 00 0 CO O OC OCD OOO0 2 O O O 15.00- 100.00 150.00 200.00 250.00 300.00 350.00 HP Portion of R Output: born aint lord salbai of eonsbivs idsibillue atsillier Analysis of Variance Table at priau Jest fico s to ORMYTO Response: CITYMPG Df Sum Sq Mean Sq F value Pr(>F) HP 409.782 409.782 106.051 0 I(HP^2) 1 952.276 952.276 246.448 O Residuals 120 463.680 3.864 c) (5 points) What percentage of students will take Call: Im(formula = CITYMPG ~ HP + I(HP^2), data = eaglecar) Coefficients: Estimate Std. Error t value Pr(> It1) (Intercept) 46.30872 1.931 23.987 8.272E-48 -0.20809 0.019 -11.004 6.095E-20 HP 1(HPA2) 0.00037 0.000 8.615 3.130E-14 Residual standard error: 1.966 on 120 degrees of freedom Multiple R-squared: 0.744, Adjusted R-squared: 0.740 F-statistic: 176.270 on 2 and 120 DF, p-value: 8.001e-07 9.4738 078 .4616 535 .4625 .4545 88 4686 4744 .4693 .4633 -4793 .4699 34 .4798 4750 4756 .4803 4808 4761 4706 1019 .4767 (7 points) Perform a test to establish if upward curvature exists in the response curve. Test using a = 0.05 . List any assumptions that you must make. noinigo JATOT ON as OS belosami el esvifsinessiqs) elela to noinigo erli ferflorw level son 1291 all Joubrios of salam leum voy enobigmuses lis laid of atport How dous the:thot the conbdance mier barney 86%? Please wouleat in a simple senied is. 11