Anova: Adjusted R-Squared
R-squared adjusted for the number of parameters in the model relative to the number of points in the design. A measure of the amount of variation about the mean explained by the model.
\[Adj. R^2 = 1 - \begin{bmatrix} \left ( \frac{SS_{residual}}{df_{residual}} \right ) / \left ( \frac{SS_{residual}\ +\ SS_{model}}{df_{residual}\ +\ df_{model}} \right ) \end{bmatrix} = 1\ -\ \begin{bmatrix} \left ( \frac{SS_{residual}}{df_{residual}} \right ) / \left ( \frac{SS_{total}\ -\ SS_{curvature} -\ SS_{block}}{df_{total}\ -\ df_{curvature} -\ df_{block}} \right ) \end{bmatrix}\]
The Adjusted R-squared and Predicted R-squared should be within approximately 0.20 of each other to be in “reasonable agreement.” If they are not, there may be a problem with either the data or the model.