Some models are linear in the parameters (for example, a quadratic or other polynomial); others can be transformed to be such (for example, when you use a log transformation of x). The Fit Model or Fit Y by X platforms are more appropriate in these situations. Example of a Regression Analysis Using Fit Model in the Fitting Linear Models book shows a significant linear relationship between oxygen uptake and time spent running. For more information about Fit Model, see Model Specification in the Fitting Linear Models book. For more information about Fit Y by X, see Introduction to Fit Y by X in the Basic Analysis book.

The Fit Curve platform enables you to fit models that are nonlinear in the parameters. The initial example in this chapter shows the analysis of a nonlinear relationship: drug toxicity as a function of concentration. The effect of concentration on toxicity changes from low to high doses, so this relationship is nonlinear.

Fit Curve also enables you to build a model to create the prediction formula. Then you set upper and lower parameter limits in Nonlinear. For details, see Example of Setting Parameter Limits in Nonlinear Regression.