second part

A simple linear regression model does not appear to be appropriate. There appears to be a curvilinear relationship between the two variables. b. The Minitab output follows: Analysis of Variance Source DF Adj SS Adj MS F-Value p-Value Regression 2 12,162,026 6,081,013 15.25 0.0005 Error 12 4,785,217 398,768 Total 14 16,947,243 Model Summary S R-sq R-sq(adj) 631.4809 71.76% 67.06% Regression Equation Price($ 1000) = 32639 - 4417 Rating + 149 RatingSq c. The Minitab output for the model using the base 10 log of Price as the dependent variable follows: Analysis of Variance Source DF Adj SS Adj MS F-Value p-Value Regression 1 3.6261 3.6261 42.94 0.0000 Error 13 1.0978 0.0844 Total 14 4.7239 Model Summary S R-sq R-sq(adj) 0.290597 76.76% 74.97% Regression Equation logPrice = -10.092 + 10.375 Rating d. The model in part (c) is preferred because it provides a better fit