Model/Curve Fitting

The curve fitting tool adjusts the chosen equation so that it comes as close as possible to your data. Each equation has a general form with a set of coefficients. A new column containing calculated y-values may be added to your data table if desired.

A tutorial covering curve fitting is available. Select Open from the File menu, then look in the Experiments folder to access it.

Curve Fits can be:

Automatic: The program will find the best values for the coefficients to fit the curve to the data whenever the user presses the "Try Fit" button.  If the program is having a difficult time fitting the data, you can enter some known starting values for the coefficients, or you can press "Try Fit" more than once. (Note that if you enter coefficient values directly, the dialog switches to Manual -- if you're giving start values for an automatic fit, you must check the Automatic radio button again)

Manual (Model): You type in all the coefficient values and the program does not do any automatic fitting.

Note: You don't need data if you simply want to see a function plotted alone on a graph.

Note: If you do an experiment that requires an equation not found on the curve fit list, you can enter the equation in the curve fit dialog yourself. Save the file. When that file is opened, the custom equation will appear in the list.
Tip: You can click on Try Fit more than once.  Each time you click Try Fit, the algorithm starts from the current values of the coefficients and iterates closer to a solution.

If you want to exclude points from the fit, return to the page, select the point or points you want to exclude in the data table, and select Strike Through Data Cells from the Edit menu. Then return to the Curve Fit dialog to perform a new fit. The selected data points will not be graphed nor used in the curve fit.
 
 

See also:

Curve Fit Dialog

Linear Fit
 
*(The Root Mean Square Error is a measure of how far away, on average, the data points are from the fitted curve. RMSE is in the units of the Y-Axis.)

RMSE =

where f(xi) is the function evaluated at the x value xi, the yi are the y values of the points, n is the number of points, and d is the number of free parameters in the function f(x).