Lecture Notes chapter 4: Curve Fitting

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 4 of the lecture notes introduces Curve Fitting using Python. In fact, one of these documents covers Curve Fitting using two different Python libraries (lmfit and scipy), however, the lmfit library is the recommended one for the Maker Lab course, as it's more user-friendly and covers most uses needed by the student projects. Thus, the other document cuts out the scipy library explanations, keeping the document shorter and easier to follow.

Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality.

Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324

Licence: Creative Commons Attribution Non Commercial Share Alike 4.0 International

Keywords: Jupyter Notebooks, Python programming, research skills, curve fitting


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