The standard error of the estimate (SEE) is the residual standard deviation in a regression, measuring typical size of prediction errors around the fitted line. Smaller SEE means the model’s fitted values track the observed dependent variable more tightly in-sample. It is not the same as the standard error of a single coefficient. Confusing SEE with R², or with a coefficient’s standard error, is a frequent mix-up.