The Effect Screening platform uses the principle of effect sparsity (Box and Meyer 1986). This principle asserts that relatively few of the effects that you study in a screening design are active. Most are inactive, meaning that their true effects are zero and that their estimates are random error.
Gives parameter estimates corresponding to factors that are scaled to have a mean of zero and a range of two. See Scaled Estimates and the Coding of Continuous Terms.
Identifies parameter estimates that deviate from normality, helping you determine which effects are active. See Normal Plot Report.