The correct answer was C) The standard error of the estimate (SEE) measures the uncertainty in the relationship between the independent and dependent variables and helps gauge the fit of the regression line (the smaller the standard error of the estimate, the better the fit). Remember that the SEE is different from the sum of squared errors (SSE). SSE = the sum of (actual value - predicted value)2. SEE is the the square root of the SSE "standardized" by the degrees of freedom, or SEE = [SSE / (n - 2)]1/2 |