In regression analysis,we can often use the standard error of estimate se to judge which of several potential regression equations is the most useful.

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The standard error of estimate (se) is a measure of the variation of the actual values of the dependent variable around the predicted values from the regression equation. The smaller the se, the better the fit of the regression equation to the data. Therefore, we can use the se to compare the usefulness of different regression equations and choose the one with the smallest se.

In Regression Analysis,we Can Often Use the Standard Error of Estimate