Burger King nutrition. Like many fast-food restaurant chains, Burger King (BK) provides data on the nutrition content of its menu items on its website. Here’s a multiple regression predicting calories for Burger King foods from Protein content (g), Total Fat (g), Carbohydrate (g), and Sodium (mg) per serving.

a) Do you think this model would do a good job of predicting calories for a new BK menu item? Why or why not?

b) The mean of Calories is 455.5 with a standard deviation of 217.5. Discuss what the value of s in the regression means about how well the model fits the data.

c) Does the value of 100.0% mean that the residuals are all actually equal to zero?

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Dependent variable is: Calories R-squared =100.0% R-squared [adjusted] = 100.0% s = 3.140 with 315 = 26 degrees of freedom Source Sum of Squares df Mean Square F-ratio Regression 1419311 Residual 256.307 4 354828 26 35994 9.85796 Variable Coeff SE(Coeff) t-ratio P-value Intercept 6.53412 2.425 2.69 0.0122 Protein 3.83855 0.0859 44.7 <0.0001 Total fat 9.14121. 0.0779 117 <0.0001 Carbs 3.94033 0.0338 117 <0.0001 Na/Serv. -0.69155 0.2970 -2.33 0.0279