I am having trouble solving these two parts. I have provided 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 points a dealership has mereecla-benz e500 for sale it and the are asking what is this car suppose we know r="214.79," sxx="712088.8." an individual with give estimate of price car. provide interpret prediction interval your estimate. may use closest degrees freedom in t-table hint: you can find s from jmp output>