Keywords
linear least squares, residual, Julia, curve fitting, polynomial
Abstract
This article is a review of the theory and practice behind linear least squares curve fitting. It outlines how to find the optimal parameters to match experimental data with theory and how to estimate the uncertainty in those parameters. The article demonstrates and validates these calculations in Excel, MATLAB, Mathematica, Python, and Julia.
BYU ScholarsArchive Citation
Turley, R. Steven, "Linear Least Squares Curve Fitting" (2018). Faculty Publications. 2322.
https://scholarsarchive.byu.edu/facpub/2322
Document Type
Peer-Reviewed Article
Publication Date
2018-09-01
Permanent URL
http://hdl.lib.byu.edu/1877/5176
Language
English
College
Physical and Mathematical Sciences
Department
Physics and Astronomy
Copyright Use Information
http://lib.byu.edu/about/copyright/