Be default LinearFit returns the values of the parameters of the fit and the errors in those parameters. The ReturnFunction option allows you to choose to view the results as an explicit function of the independent variable.
For example, here is the result of a fit to a parabolic function of the independent variable of some data on the growth of the retina in the cat:
| var.names/data.val **** Fit Number 1 **** CP with no error versus area with no error A0 = 2.56 ± 0.25 A2 = 0.000757 ± 0.000032 Sum of Squares = 5.75043 for 12 degrees of freedom (Assumed statistical error in the dependent variable: 0.69224) |
 |
Here is a snapshot of the relevant part of the Fit Options screen with the ReturnFunction option set to True.
The result of the fit is now:
| var.names/data.val **** Fit Number 2 **** CP with no error versus area with no error (ReturnFunction True) CP = 2.56 + 0.000757 area2 with error: 0.25 - 0.000032 area2 Sum of Squares = 5.75043 for 12 degrees of freedom (Assumed statistical error in the dependent variable: 0.69224) |
|
The first function returned is the one that best fits the data. The second function is the estimated error in the function.
This help document is Copyright © 1999 David M. Harrison. The sample screens are Copyright © 1999 Solomon R.C. Douglas and David M. Harrison. This is version 1.2 of the help document, date (m/d/y) 11/25/99.