Curve fitting is finding a curve which matches a series of data points and possibly other constraints. It is most often used by scientists and engineers to visualize and plot the curve that best describes the shape and behavior of their data.

Nonlinear curve fitting is an iterative process that may converge to find a best possible solution. It begins with a guess at the parameters, checks to see how well the equation fits, the continues to make better guesses until the differences between the residual sum of squares no longer decreases significantly. For complicated curve fitting problems, use SigmaPlot’s Dynamic Fit Wizard to find the best solution.

- The Dynamic Fit Wizard automates the search for initial parameter values that lead to convergence to the best possible solution.
- Like the Regression Wizard, the Dynamic Fit Wizard is a step-by-step guide through the curve fitting procedures, but with an additional panel in which you set the search options (in the figure below).

Please note that the Dynamic Fit Wizard is especially useful for more difficult curve fitting problems with three or more parameters and possibly a large amount of variability in the data points. For linear regressions or less difficult problems, such as simple exponential two parameter fits, the Dynamic Fit Wizard is overkill and you should be using the Regression Wizard.