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.

Document Type

Peer-Reviewed Article

Publication Date

2018-09-01

Language

English

College

Physical and Mathematical Sciences

Department

Physics and Astronomy

University Standing at Time of Publication

Full Professor

Included in

Physics Commons

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