1962 Ferrari 250 GTO 1967-1968 Ferrari 275 GTB/4 NART Spyder 1968-1973 Ferrari 365 GTB/4 Daytona 1962-1967 Jaguar E-type OTS 1969-1971 Jaguar E-type Series II OTS 1971-1974 Jaguar E-type Series III OTS 1951-1954 Jaguar XK 120 roadster (steel) 1950-1953 Jaguar XK C-type 1956-1957 Jaguar XKSS 18 17 17 15 14 16 17 16 13 425.0 410.0 170.0 75.0 67.0 130.0 440.0 250.0 70.0 Rating? log(Rating) Part b O oo O o co co #N/A #N/A #N/A #N/A #N/A Rating 18 19 18 19 16 19 18 17 17 15 14 16 17 16 13 Price ($1000) log(Price) Formula 1550.0 #N/A 3800.0 950.0 1350.0 320.0 2800.0 425.0 #N/A 410.0 #N/A 170.0 75.0 #N/A 67.0 #N/A 130.0 440.0 #N/A 250.0 70.0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A VA #N/A #N/A b. Develop an estimated multiple regression equation with x = rarity rating and x2 as the two independent variables. Price = + Rating + Rating? (to whole numbers) What is the value of the coefficient of determination? Note: report R2 between 0 and 1. (to 3 decimals) What is the value of the F test statistic? (to 2 decimals) What is the p-value? (to 4 decimals) C. Consider the nonlinear relationship shown by equation E(y) = Bo Bi. Use logarithms to develop an estimated regression equation for this model. log(Price) = + log(Rating) (to 3 decimals) What is the value of the coefficient of determination? Note: report R2 between 0 and 1. (to 3 decimals) What is the value of the F test statistic? (to 2 decimals) What is the p-value? (to 4 decimals) d. Do you prefer the estimated regression equation developed in part (b) or part (C)? Explain. The model in part A is preferred because it provides a better fit. 1962 Ferrari 250 GTO 1967-1968 Ferrari 275 GTB/4 NART Spyder 1968-1973 Ferrari 365 GTB/4 Daytona 1962-1967 Jaguar E-type OTS 1969-1971 Jaguar E-type Series II OTS 1971-1974 Jaguar E-type Series III OTS 1951-1954 Jaguar XK 120 roadster (steel) 1950-1953 Jaguar XK C-type 1956-1957 Jaguar XKSS 18 17 17 15 14 16 17 16 13 425.0 410.0 170.0 75.0 67.0 130.0 440.0 250.0 70.0 Rating? log(Rating) Part b O oo O o co co #N/A #N/A #N/A #N/A #N/A Rating 18 19 18 19 16 19 18 17 17 15 14 16 17 16 13 Price ($1000) log(Price) Formula 1550.0 #N/A 3800.0 950.0 1350.0 320.0 2800.0 425.0 #N/A 410.0 #N/A 170.0 75.0 #N/A 67.0 #N/A 130.0 440.0 #N/A 250.0 70.0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A VA #N/A #N/A b. Develop an estimated multiple regression equation with x = rarity rating and x2 as the two independent variables. Price = + Rating + Rating? (to whole numbers) What is the value of the coefficient of determination? Note: report R2 between 0 and 1. (to 3 decimals) What is the value of the F test statistic? (to 2 decimals) What is the p-value? (to 4 decimals) C. Consider the nonlinear relationship shown by equation E(y) = Bo Bi. Use logarithms to develop an estimated regression equation for this model. log(Price) = + log(Rating) (to 3 decimals) What is the value of the coefficient of determination? Note: report R2 between 0 and 1. (to 3 decimals) What is the value of the F test statistic? (to 2 decimals) What is the p-value? (to 4 decimals) d. Do you prefer the estimated regression equation developed in part (b) or part (C)? Explain. The model in part A is preferred because it provides a better fit