What is the difference between standard error of estimate and standard error of the regression?

Standard error of estimate (SEE) measures the average error in predicting the dependent variable based on the independent variable(s). Standard error of the regression measures the variability of the regression coefficients themselves (i.e., how much the coefficients might change if the data were slightly different). SEE focuses on the prediction error, while the standard error of the regression focuses on the stability of the regression model.