A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.
The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y=f(x), and is well suited to fast, reliable analysis of data in all fields of biology.
Brown
A M
AM
Department of Neurology, Box 356465, University of Washington School of Medicine, Seattle, WA 98195-6465, USA. ambrown@u.washington.edu
D019295:Computational Biology; D003627:Data Interpretation, Statistical; D003628:Database Management Systems; D016018:Least-Squares Analysis; D017711:Nonlinear Dynamics; D012044:Regression Analysis; D012984:Software