Adequate Precision

This is a signal-to-noise ratio. It compares the range of the predicted values at the design points to the average prediction error. Ratios greater than 4 indicate adequate model discrimination.

Where,

$\hat{Y}$ are the predictions at the run settings

$p\hat{\sigma}^2$ is the residual mean square from ANOVA table.

$p$ is the number of terms in the model.

$n$ is the number of runs in the design.