2) Does weight affect city miles per gallon? An engineer working at Ford Motor Company collected a random sample of different models of cars, and found the weight and city miles per gallon of each. Determine the following: a) What is the explanatory variable? What is the response variable? b) What is the least squares regression equation? c) What is the coefficient of determination, r?? Interpret this result. d) What is the correlation coefficient, r? Interpret this result. e) Are there any outliers or influential observations? (Write the observation number or write N/A.) If so, which observations are outliers? which are influential? f) The weights of the cars ranged from 2469 to 6400 pounds. i) What would be the predicted city mpg of a car that is 2300 pounds? i) What would be the predicted city mpg of a car that is 4800 pounds? Regression Analysis: City Mpg versus Weight Regression Equation City Mpg = 38.24 - 0.004855 Weight Fits and Diagnostics for Unusual Observations Coefficients Obs City Mpg Fit Resid Std Resid Term Coef SE Coef T-Value P-Value VIF m Constant 38.24 2.30 16.62 0.000 : : : : Weight -0.004855 0.000589 -8.24 0.000 1.00 45 12.00 21.69 -9.69 -209 R X Model Summary 75 11.00 7.17 3.83 0.87 X s R-sq R-sg(adj) R-sq(pred) 466884 45.30% 44.63% 42.06% 78 17.00 8.92 8.08 1.82 X Analysis of Variance R Large residual Source ' DF AdjSS AdjMS F-Value P-Value X Unusual X Regression 1 1480.31 1480.31 67.91 0.000 Weight 1 1480.31 1480.31 67.91 0.000 Error 82 1787.44 21.80 Lack-of-Fit 74 1767.11 23.88 9.40 0.001 Pure Error 8 20.33 2.54 Total 83 3267.75