We saw in Chapter 7 that the calorie count of a breakfast cereal is linearly associated with its sugar content. Can we predict the calories of a serving from its vitamin and mineral content? Here's a multiple regression model of Calories per serving on its Sodium (mg), Potassium (mg), and Sugars (g):

Assuming that the conditions for multiple regression are met,
a) What is the regression equation?
b) Do you think this model would do a reasonably good job at predicting calories? Explain.
c) Would you consider removing any of these predictor variables from the model? Why or why not?
d) To check the conditions, what plots of the data might you want to examine?

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Dependent variable is: Calories R-squared 38.4% R-squared (adjusted)--35.9% s 15.60 with 77 4 73 degrees of freedom Source Sum of Squares dF Mean Square F-ratio P-value Regression 11091.8 3 3697.28 15.2 <0.0001 Residual 7760 73 243.289 Variable Coefficient SE(Coeff) t-ratio P-value Intercept 83.0469 5.198 160 <0.0001 Sodium 0.0572 0.0215 2.67 0.0094 Potass 0.01933 0.0251-0.769 0.4441 Sugars 2.38757 0.4066 5.87 <0.0001