A consumer advocacy group recorded several variables on 140 models of cars. The resulting information was used to produce two models for predicting miles per gallon in the city (mpg_city), one based on the engine displacement (in cubic inches) and a second one based the power of the engine (in horsepower). Model 1: mpg vs engine displacement The regression equation is mpg_city=33.1 - 0.0625*displacement S = 3.25243 R-squared = 66.5% Model 2: mpg vs horsepower The regression equation is mpg_city=32.1 - 0.0574*horsepower S = 3.5536 R-squared = 60.5% The displacement variable is better because it has a lower estimate for the residual standard error (S=3.25243).

The variable horsepower is better because it has a higher residual standard error (S=3.5536).

The variable horsepower is better because it has a higher residual standard error (S=3.5536) and a lower R-square (60.5%).

The displacement variable is better because it has a higher R-square (66.5%).

The displacement variable is better because it has a lower estimate for the residual standard error (S=3.25243) and a higher R-square (66.5%).