Is it possible for the standard error of the estimate to actually increase if variables are added to the model that do not aid in explaining the variation in the dependent variable?
The standard error of the estimate(S.E.est) is a measure of the variability of predictions in a regression. Therefore, the standard error of the estimate is a measure of the dispersion (or variability) in the predicted scores in a regression.
The smaller the value of a standard error of estimate the closer are the dots to the regression line and better is the estimate based on the equation of the line. If the standard error is zero, then there is no variation corresponding to the computed line and the correlation will be perfect.
If good variables added to regression model then it decreases the standard error of estimate .
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