About
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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The talk
Credits and licence
- Institution
- CERN
- Department
- LPCC Workshops
- Taught by
- Giordon Holtsberg Stark, Lukas Alexander Heinrich, Matthew Feickert
- Year
- 2021
- Language
- English
- Subjects
- Physics
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed