linear least squares, residual, Julia, curve fitting, polynomial
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.
Physical and Mathematical Sciences
Physics and Astronomy
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