AI Engineering Degree Practice Exam 2026 - Free AI Engineering Practice Questions and Study Guide

To calculate the predicted value for "Co2Emission," you would typically use the linear regression formula:

\[ \text{Predicted Value} = \text{Intercept} + (\text{Coefficient} \times X1) \]

In this scenario, the intercept is given as 100, and the coefficient for the variable \( X1 \) (number of cylinders) is 30. To find the predicted value, we need the actual number of cylinders, designated as \( X1 \). Assuming \( X1 \) is 4, the calculation would be:

\[ \text{Predicted Value} = 100 + (30 \times 4) \]

\[ = 100 + 120 \]

\[ = 220 \]

Thus, the predicted value for "Co2Emission" when there are 4 cylinders is indeed 220. This indicates a direct relationship between the number of cylinders and carbon dioxide emissions, with 30 units of emission contributed for each additional cylinder, starting from a base emission of 100 units. The correct calculation confirms that the prediction of 220 aligns with the parameters given.