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| Non-Linear Least Squares Regression© | ||||||||||||||||||||||||
| Sidney H. Young **Sid Young died in 2004 after a long illness. He was a beloved teacher and a leader in the development and use of Mathcad as a tool to promote student learning in physical chemistry. A memorial to Dr. Young was established by the University of South Alabama ACS Student Affiliate, http://www.southalabama.edu/acs/memorial.html | ||||||||||||||||||||||||
| Andrzej Wierzbicki Department of Chemistry University of South Alabama Mobile, AL 36688 United States mail to: wierzb@andy.chem.usouthal.edu | ||||||||||||||||||||||||
| Abstract | ||||||||||||||||||||||||
| Nonlinear least squares regression is often required in the Physical Chemistry Laboratory. This template demonstrates various implicit and explicit methods for determination of the parameters of the regressed curve. It will produce standard deviation of fit, and standard deviations of the parameters. Residual analysis is used to demonstrate techniques of removing bad data points from the fit. Data may be read into the template by editing in a Read statement. Minor editing will then let the template be used for a variety of applications. As in the previous template, Linear Least Squares Regression, the parameters will be tested to see if their addition in the model is statistically significant. (The Mathcad 6 and Mathcad 7 versions are identical except for the subscripts in the first graph.) | ||||||||||||||||||||||||
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| Comments to: Andrzej Wierzbicki at wierzb@andy.chem.usouthal.edu | ||||||||||||||||||||||||
| ©Copyright 2004 Journal of Chemical Education | ||||||||||||||||||||||||
