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Introduction to statistics in metrology

This book provides an overview of the application of statistical methods to problems in metrology, with emphasis on modelling measurement processes and quantifying their associated uncertainties. It covers everything from fundamentals to more advanced special topics, each illustrated with case studi...

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Detalles Bibliográficos
Autores principales: Crowder, Stephen, Delker, Collin, Forrest, Eric, Martin, Nevin
Lenguaje:eng
Publicado: Springer 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-53329-8
http://cds.cern.ch/record/2746915
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author Crowder, Stephen
Delker, Collin
Forrest, Eric
Martin, Nevin
author_facet Crowder, Stephen
Delker, Collin
Forrest, Eric
Martin, Nevin
author_sort Crowder, Stephen
collection CERN
description This book provides an overview of the application of statistical methods to problems in metrology, with emphasis on modelling measurement processes and quantifying their associated uncertainties. It covers everything from fundamentals to more advanced special topics, each illustrated with case studies from the authors' work in the Nuclear Security Enterprise (NSE). The material provides readers with a solid understanding of how to apply the techniques to metrology studies in a wide variety of contexts. The volume offers particular attention to uncertainty in decision making, design of experiments (DOEx) and curve fitting, along with special topics such as statistical process control (SPC), assessment of binary measurement systems, and new results on sample size selection in metrology studies. The methodologies presented are supported with R script when appropriate, and the code has been made available for readers to use in their own applications. Designed to promote collaboration between statistics and metrology, this book will be of use to practitioners of metrology as well as students and researchers in statistics and engineering disciplines.
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spelling cern-27469152021-04-21T16:44:17Zdoi:10.1007/978-3-030-53329-8http://cds.cern.ch/record/2746915engCrowder, StephenDelker, CollinForrest, EricMartin, NevinIntroduction to statistics in metrologyMathematical Physics and MathematicsThis book provides an overview of the application of statistical methods to problems in metrology, with emphasis on modelling measurement processes and quantifying their associated uncertainties. It covers everything from fundamentals to more advanced special topics, each illustrated with case studies from the authors' work in the Nuclear Security Enterprise (NSE). The material provides readers with a solid understanding of how to apply the techniques to metrology studies in a wide variety of contexts. The volume offers particular attention to uncertainty in decision making, design of experiments (DOEx) and curve fitting, along with special topics such as statistical process control (SPC), assessment of binary measurement systems, and new results on sample size selection in metrology studies. The methodologies presented are supported with R script when appropriate, and the code has been made available for readers to use in their own applications. Designed to promote collaboration between statistics and metrology, this book will be of use to practitioners of metrology as well as students and researchers in statistics and engineering disciplines.Springeroai:cds.cern.ch:27469152020
spellingShingle Mathematical Physics and Mathematics
Crowder, Stephen
Delker, Collin
Forrest, Eric
Martin, Nevin
Introduction to statistics in metrology
title Introduction to statistics in metrology
title_full Introduction to statistics in metrology
title_fullStr Introduction to statistics in metrology
title_full_unstemmed Introduction to statistics in metrology
title_short Introduction to statistics in metrology
title_sort introduction to statistics in metrology
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-030-53329-8
http://cds.cern.ch/record/2746915
work_keys_str_mv AT crowderstephen introductiontostatisticsinmetrology
AT delkercollin introductiontostatisticsinmetrology
AT forresteric introductiontostatisticsinmetrology
AT martinnevin introductiontostatisticsinmetrology