The GraphPad Guide to Nonlinear Regression

The GraphPad Guide to Nonlinear Regression Dr. Harvey Motulsky, President, GraphPad Software Copyright © 1995 – 2001 by GraphPad Software, Inc. All rights reserved.
This booklet explains the principles of nonlinear regression. It will help you decide when to use nonlinear regression, how to make appropriate decisions when using a nonlinear regression program, and how to interpret the results. It is written for scientists, not statisticians, so contains very little math. View the guide in your web browser. Or download the .pdf (printer-ready file) file now (397kB).	Contents Introduction to nonlinear regression Introduction to nonlinear regression Why you should use nonlinear regression How nonlinear regression works Decisions you need to make when fitting curves with nonlinear regression Interpreting nonlinear regression results Assumptions of nonlinear regression Variables, standard errors, and confidence intervals Sum-of-squares, sy.x, and R 2 Residuals and the runs test How to tell if the nonlinear regression fit is any good What to do when the fit is no good Comparing two equations Comparing fits to two data sets
More information on nonlinear regression: GraphPad Guide to Analyzing Radioligand Binding Data (40 pages). Our web site, curvefit.com , which has far more detailed information that this Guide. It includes general information on nonlinear regression, as well as its application to analyzing radioligand binding, enzyme kinetic, and dose-response data. Nonlinear regression links. Learn more about our program, GraphPad Prism; the best general-purpose nonlinear regression program for Windows and Mac.
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