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An Open-Source, Cross-Platform Resource for Nonlinear Least-Squares Curve Fitting

Title data

Möglich, Andreas:
An Open-Source, Cross-Platform Resource for Nonlinear Least-Squares Curve Fitting.
In: Journal of Chemical Education. (9 October 2018) . - Article ASAP.
ISSN 1938-1328
DOI: https://doi.org/10.1021/acs.jchemed.8b00649

Project information

Project financing: Alexander von Humboldt-Stiftung
Deutsche Forschungsgemeinschaft

Abstract in another language

The quantitative evaluation of experimental data and their graphical presentation are integral to teaching and research in chemistry and the life sciences. Data are commonly fitted to physical models, which in all but the simplest cases are expressed as nonlinear mathematical functions. To facilitate data evaluation in both teaching and research contexts, the Fit-o-mat program, implemented in Python, offers versatile nonlinear least-squares curve fitting through a graphical user interface. Fit-o-mat supports near-arbitrary fitting functions, including numerical and discontinuous ones, produces vectorized graphics, runs on different operating systems, and is free of charge, thus promoting the adoption of the program by students and instructors in the classroom and beyond. An embedded tutorial mode facilitates integration of Fit-o-mat into teaching curricula at the undergraduate and graduate levels.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry > Chair Biochemistry > Chair Biochemistry - Univ.-Prof. Dr. Andreas Möglich
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry > Chair Biochemistry
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 570 Life sciences, biology
Date Deposited: 10 Oct 2018 09:46
Last Modified: 10 Oct 2018 09:46
URI: https://eref.uni-bayreuth.de/id/eprint/46006