Linear regression model evaluation begins with scoring a table that includes the actual values of the dependent variable. The standard error of estimate for the model is calculated and reported and may be compared to the standard error of estimate reported when the model was built. The standard error of estimate is calculated as the square root of the average squared residual value over all the observations, i.e.
where 
is the actual value of the dependent variable, y is its predicted value, n is the number of observations, and p is the number of independent variables (substituting n-p in the denominator if there is no constant term).