Dortmund 2021 – scientific programme
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T: Fachverband Teilchenphysik
T 68: Neutrino physics without accelerators III
T 68.6: Talk
Wednesday, March 17, 2021, 17:20–17:35, Tr
Statistical methods for the final data analysis of GERDA — •Lolian Shtembari1, Allen Caldwell1, Matteo Agostini2, and Oliver Schulz1 for the GERDA collaboration — 1Max Planck Institute for Physics, Munich, Germany — 2Department of Physics and Astronomy, University College London, London, UK
The GERmanium Detector Array (GERDA) experiment investigated the Majorana nature of neutrinos by searching for the lepton-number-violating neutrinoless double-β (0νββ) decay of 76Ge. We present the statistical analysis of the data collected during all of GERDA's operational time. Through Bayesian Hierarchical modelling we investigated some challenging key aspects in the search for rare-processes: evaluating the discovery potential power, the limit setting power on the signal rate and the goodness of fit of the background for models with data sets consisting of a small number of events. The topics selected include the systematic variations in the results due to the choice of fit models. Order statistics and the Bayes factor are used as tools to study the background goodness of fit and the signal discovery potential.