Interpreting comparison of models

Reality check before statistics

Apply a common sense reality check before looking at any statistical approach to comparing fits. If one of the fits has results that are scientifically invalid, then accept the other model. Only when both fits make scientific sense should you use statistical method to compare the two fits .

Prism partially automates this 'reality check' approach. If the fit of either model is ambiguous, then Prism chooses the other model without performing any statistical test.

Statistical approaches balance the change in sum-of-squares with the change in numbers of degrees of freedom

The more complicated model (the one with more parameters) almost always fits the data better than the simpler model. Statistical methods are needed to see if this difference is enough to prefer the more complicated model. Prism can do this via the extra sum-of-squares F test or using information theory and computation of AIC.