(f) (3 points) Comment on the residual by X plot. Does a linear regression seem appro- priate? Are there any concerns? (g) (6 points) Suppose we know I = 214.79, Sxx = 712088.8. For an individual car with horsepower 350, give an estimate of the price of the car. Provide and interpret a 95% prediction interval for your estimate. (You may use the closest degrees of freedom in the t-table). Hint: you can find S,, from the JMP output.Cars JMP Output -Bivariate Fit of SuggestedRetailPrice By Horsepower 120000 100000 80000 SuggestedRetail Price 60000 40000 20000 50 100 150 200 250 300 350 400 450 500 Horsepower - Linear Fit Linear Fit SuggestedRetailPrice = -10546.13 + 197.89293*Horsepower Summary of Fit ASquare 0.771197 ASquare Adj 0.769539 Root Mean Square Error 7742.946 Mean of Response 31959.86 Observations (or Sum Wgts) 140 * Lack Of Fit * Analysis of Variance Parameter Estimates Term Estimate Std Error t Ratio Probelt) Intercept -10546.13 2076.676 -5.08 <.0001 horsepower residual by x plot suggested retailprice>