Statistics tools for teaching at NBI
Statistical tools for teaching at NBI
- Reporting scientific results, including proper rounding
- Tabulation of data useful in Jupyter Notebooks
- Visualisation of data in 1 and many dimensions
- Robust calculations of sample means, variances, and covariances, for unweighted and weighted samples. For weighted samples, both frequency and non-frequency weights are supported.
- Sampling of arbitrary PDFs
- Curve fitting using
- Linear least squares
- Non-linear least squares
- Maximum likelihood estimates
- Representation of fit confidence contours
Examples of use
This notebook gives examples of use.
Booklet on Statistics with Python
The booklet Statistics Overview - With Python lays out much of the theoretical foundation for the tools available.
Application Programming Interface Documentation
The API is documented.
2019 © Christian Holm Christensen
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