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.
Dependent variable is: Calories
R-squared = 100.0% R-squared [adjusted] = 100.0% s = 3.140 with 31 - 5 = 26 degrees of freedom
Source Sum of Squares df Mean Square F-ratio
Regression 1419311 4 354828 35994
Residual 256.307 26 9.85796
a) Do you think this model would do a good job of predict- ing 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 R2 value of 100.0% mean that the residuals are all actually equal to zero?
|
Variable
Intercept
|
Coeff
6.53412
|
SE(Coeff)
2.425
|
t-ratio
2.69
|
P-value
0.0122
|
|
Protein
|
3.83855
|
0.0859
|
44.7
|
6 0.0001
|
|
Total fat
|
9.14121
|
0.0779
|
117
|
6 0.0001
|
|
Carbs
|
3.94033
|
0.0338
|
117
|
6 0.0001
|
|
Na/Serv.
|
- 0.69155
|
0.2970
|
- 2.33
|
0.0279
|