We saw in Chapter 7 that the calorie content of a breakfast cereal is linearly associated with its sugar content. Is that the whole story? Here's the output of a regression model that regresses Calories for each serving on its Protein(g), Fat(g), Fiber(g), Carbohydrate(g), and Sugars(g) content.

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) To check the conditions, what plots of the data might you want to examine?
d) What does the coefficient of Fat mean in this model?

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Dependent variable is: Calories R-squared 93.6% R-squared (adjusted) 93.1% s # 5.113 with 77-6-71 degrees of freedom Source Sum of Squares df Mean Square F-ratio Regression 269959 Residual 5 5399.18 207 1856.03 7 26.1412 Variable Coefficient SE(Coeff) t-ratio P-value Intercept-0.879994 4.383 -0.20 0.8414 Protein 3.60495 0.6977 5.17 <0.0001 Fat Fiber Carbo 4.13 Sugars 4.00677 0.1719 23.3 <0.0001 8.56877 0.6625 9 <0.0001 0.309180 0.3337 0.927 3.572 996 0.2049 20 <0.0001