# pyhf: pure-python HistFactory -- the tutorial

- Institution: CERN
- Department: LPCC Workshops
- Taught by: Giordon Holtsberg Stark, Lukas Alexander Heinrich, Matthew Feickert
- Year: 2021
- Language: English
- Subjects: Physics
- Source: [CERN](https://videos.cern.ch/record/3012607)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

The HistFactory p.d.f. template \[CERN-OPEN-2012-016\]\[1\] is per-se independent of its implementation in ROOT and sometimes, it's useful to be able to run statistical analysis outside of ROOT, RooFit, RooStats framework. This tutorial will introduce users (who are generally familiar with hypothesis testing) to the \[`pyhf`\]\[2\] python package. Examples using public \[HEPData\]\[3\] material will be used for asymptotic fits, brazil bands, and pull plots. By the end of the tutorial, users will understand how to find likelihoods on HEPData, how to download and perform hypothesis testing, how to patch in a signal into a background-only pdf, and how to simplify likelihoods.

\[1\]: https://cds.cern.ch/record/1456844 \[2\]: https://scikit-hep.org/pyhf/ \[3\]: https://www.hepdata.net/.

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## Lectures

1. [pyhf: pure-python HistFactory -- the tutorial](https://invisiblenetwork.ai/learn/cern/3012607/86290ba02c15), 1 h 4 min (CERN's player)