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Statistical methods for data analysis in particle physics

This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder fr...

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Detalles Bibliográficos
Autor principal: Lista, Luca
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-20176-4
http://cds.cern.ch/record/2034458
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author Lista, Luca
author_facet Lista, Luca
author_sort Lista, Luca
collection CERN
description This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data
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spelling cern-20344582021-04-21T20:09:09Zdoi:10.1007/978-3-319-20176-4http://cds.cern.ch/record/2034458engLista, LucaStatistical methods for data analysis in particle physicsMathematical Physics and MathematicsThis concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual dataSpringeroai:cds.cern.ch:20344582015
spellingShingle Mathematical Physics and Mathematics
Lista, Luca
Statistical methods for data analysis in particle physics
title Statistical methods for data analysis in particle physics
title_full Statistical methods for data analysis in particle physics
title_fullStr Statistical methods for data analysis in particle physics
title_full_unstemmed Statistical methods for data analysis in particle physics
title_short Statistical methods for data analysis in particle physics
title_sort statistical methods for data analysis in particle physics
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-20176-4
http://cds.cern.ch/record/2034458
work_keys_str_mv AT listaluca statisticalmethodsfordataanalysisinparticlephysics