When the actual values y of a dependent variable and the corresponding predicted values are the same, the standard error of estimate s_{$\varepsilon$} will be 0.0.

Question

Quizplus · Accepted Answer

When the actual values y of a dependent variable and the corresponding predicted values are the same, the residual error (also known as the residual or error term) ε will be 0. However, the standard error of estimate (which is a measure of the variability of the residuals around the regression line) is calculated by taking the square root of the sum of squared residuals divided by the degrees of freedom. Even if the residual error is 0, there will still be degrees of freedom (n - 2 for simple linear regression) and therefore a non-zero value for the standard error of estimate. So the statement is false.

When the Actual Values Y of a Dependent Variable and the Corresponding