When making predictions using a linear prediction rule,the baseline number that is added to each prediction is
A)a.
B)b.
C)X.
D)Ŷ.

Question

Quizplus · Accepted Answer

The baseline number in a linear prediction rule, often represented in the equation Ŷ = a + bX, is 'a'. This value represents the y-intercept in a linear regression model, which is the point where the line crosses the y-axis. This means when X=0, Ŷ would equal to 'a', making it the baseline number added to each prediction.

When Making Predictions Using a Linear Prediction Rule,the Baseline Number