In Exercise 19, we raised questions about two gourmet pizzas. After removing them, the resulting regression looks like this.

A plot of the residuals against the predicted values for this regression looks like this. It has been colored according to the Type of pizza.

a) What does this plot say about how the regression model deals with these two types of pizza? We constructed another variable consisting of the indicator variable Type multiplied by Calories. Here€™s the resulting regression.

b) Interpret the coefficient of Type*Cals in this regression model.
c) Is this a better regression model than the one in Exercises 17 and 19?

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Dependeทt variable is: Score R-squared-64.4% R-squared (adjusted)-59.8% s 14.41 with 27 -423 degrees of freedom Source Regression 8649.29 Res fdua 4774.56 Sum of Squares df Mean Square F-ratio 3 2883.10 23 207.590 13.9 Variable Coeff Intercept -363. 109 72.15 Calories Type 1.56772 0.2824 25.1540 6.214 -8.82748 1.887 SE(Coeff) t-ratio P-value -5.03 0.0001 5.55 . 0001 0.0005 0.0001 4.05 -4.68 50 + 25-t -25 T 25 50 75 100 Predicted -Cheese -Pepperoni Dependent variable is: Score R-squared-73.1% R-squared (adjusted)-68.2% s= 12.82 with 27-5=22 degrees of freedom Source Regression 9806.53 Residua 3617.3 Variable Coeff Sum of Squares df Mean Square F-ratio 4 2451.63 22 164.424 14.9 SE(Coeff) t-ratio P-value -6.22 0.0001 6.76 <0.0001 0.0057 -5.84 <0.0001 0.0145 Intercept -464.49874.73 Calories 1.92005 0.2842 183.634 59.99 -10.3847 1.779 уре 3.06 Type Cals 0.414960.1740 2.65