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Statistics for the LHC: Quantifying our Scientific Narrative (1/4)
<!--HTML-->Now that the LHC physics program is well under way and results have begun to pour out of the experiments, the statistical methodology used for these results is a hot topic. This is a challenge at the LHC, as we have sensitivity to discover new physics in a stage of the experiments...
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Lenguaje: | eng |
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2011
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Acceso en línea: | http://cds.cern.ch/record/1345710 |
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author | Cranmer, Kyle |
author_facet | Cranmer, Kyle |
author_sort | Cranmer, Kyle |
collection | CERN |
description | <!--HTML-->Now that the LHC physics program is well under way and results have begun to pour out of the experiments, the statistical methodology used for these results is a hot topic. This is a challenge at the LHC, as we have sensitivity to discover new physics in a stage of the experiments where systematic uncertainties can still be quite large. The emphasis of these lectures is how we can translate the scientific narrative of why we think we know what we know into quantitative statistical statements about the presence or absence of new physics. Topics will include statistical modeling, incorporation of control samples to constrain systematics, and Bayesian and Frequentist statistical tests that are capable of answering these questions. |
id | cern-1345710 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2011 |
record_format | invenio |
spelling | cern-13457102022-11-03T08:15:56Zhttp://cds.cern.ch/record/1345710engCranmer, KyleStatistics for the LHC: Quantifying our Scientific Narrative (1/4)Statistics for the LHC: Quantifying our Scientific Narrative (1/4)Academic Training Lecture Regular Programme<!--HTML-->Now that the LHC physics program is well under way and results have begun to pour out of the experiments, the statistical methodology used for these results is a hot topic. This is a challenge at the LHC, as we have sensitivity to discover new physics in a stage of the experiments where systematic uncertainties can still be quite large. The emphasis of these lectures is how we can translate the scientific narrative of why we think we know what we know into quantitative statistical statements about the presence or absence of new physics. Topics will include statistical modeling, incorporation of control samples to constrain systematics, and Bayesian and Frequentist statistical tests that are capable of answering these questions.oai:cds.cern.ch:13457102011 |
spellingShingle | Academic Training Lecture Regular Programme Cranmer, Kyle Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title | Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title_full | Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title_fullStr | Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title_full_unstemmed | Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title_short | Statistics for the LHC: Quantifying our Scientific Narrative (1/4) |
title_sort | statistics for the lhc: quantifying our scientific narrative (1/4) |
topic | Academic Training Lecture Regular Programme |
url | http://cds.cern.ch/record/1345710 |
work_keys_str_mv | AT cranmerkyle statisticsforthelhcquantifyingourscientificnarrative14 |