Standard Error of the Estimate (1 of 3)
The standard error of the estimate is a measure of the accuracy of
predictions made with a
regression line.
Consider the following data.
The
second column (Y) is predicted by the first column (X). The
slope and
Y intercept of the regression
line are 3.2716 and 7.1526 respectively. The third column, (Y'), contains
the predictions and is computed according to the formula:
Y' = 3.2716X
+ 7.1526.
The fourth column (Y-Y') is the error of prediction. It is
simply the difference between what a subject's actual score was (Y)
and what the predicted score is (Y').
The sum of the errors of prediction
is zero. The last column, (Y-Y')², contains the squared errors
of prediction.