The best linear prediction rule is the one that has the least
A)error when predicting from the mean.
B)squared error when predicting from the mean.
C)error when predicting using that rule.
D)squared error when predicting using that rule.

Question

Quizplus · Accepted Answer

The best linear prediction rule is considered the one that minimizes the squared error when predicting using that rule. This approach is fundamental in regression analysis, where the goal is to find the line (or hyperplane in higher dimensions) that minimizes the sum of the squared differences between the observed values and the values predicted by the model. This criterion is known as the least squares method.

The Best Linear Prediction Rule Is the One That Has