In a linear regression model, the relationship between variables is typically expressed in terms of coefficients. If fat content is one of the variables and the model indicates how changes in fat affect calorie count, then the coefficient for fat would show the change in calories for each additional gram of fat.
To determine the approximate increase in calories for every additional 5 grams of fat, you would multiply the coefficient for fat by 5. For example, if the coefficient for fat is 9 calories per gram, then for an additional 5 grams of fat, the increase in calories would be:
\[ \text{Increase in calories} = \text{Coefficient for fat} \times 5 \]
Using the hypothetical coefficient:
\[ \text{Increase in calories} = 9 , \text{calories/gram} \times 5 , \text{grams} = 45 , \text{calories} \]
You would need to provide the specific coefficient for fat from your regression model to calculate the exact increase in calories.