Securing the Empirical Value of Measurement Results

Securing the Empirical Value of Measurement Results Abstract Reports of quantitative experimental results often distinguish between the statistical uncertainty and the systematic uncertainty that characterize measurement outcomes. This paper discusses the practice of estimating systematic uncertainty in high-energy physics (HEP). The estimation of systematic uncertainty in HEP should be understood as a minimal form of quantitative robustness analysis. The secure evidence framework is used to explain the epistemic significance of robustness analysis. However, the empirical value of a measurement result depends crucially not only on the resulting systematic uncertainty estimate, but on the learning aims for which that result will be used. Important conceptual and practical questions regarding systematic uncertainty assessment call for further investigation. © The Author 2017. Published by Oxford University Press on behalf of British Society for the Philosophy of Science. All rights reserved. For Permissions, please email: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The British Journal for the Philosophy of Science Oxford University Press

Securing the Empirical Value of Measurement Results

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Publisher
Oxford University Press
Copyright
© The Author 2017. Published by Oxford University Press on behalf of British Society for the Philosophy of Science. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
0007-0882
eISSN
1464-3537
D.O.I.
10.1093/bjps/axx036
Publisher site
See Article on Publisher Site

Abstract

Abstract Reports of quantitative experimental results often distinguish between the statistical uncertainty and the systematic uncertainty that characterize measurement outcomes. This paper discusses the practice of estimating systematic uncertainty in high-energy physics (HEP). The estimation of systematic uncertainty in HEP should be understood as a minimal form of quantitative robustness analysis. The secure evidence framework is used to explain the epistemic significance of robustness analysis. However, the empirical value of a measurement result depends crucially not only on the resulting systematic uncertainty estimate, but on the learning aims for which that result will be used. Important conceptual and practical questions regarding systematic uncertainty assessment call for further investigation. © The Author 2017. Published by Oxford University Press on behalf of British Society for the Philosophy of Science. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Journal

The British Journal for the Philosophy of ScienceOxford University Press

Published: Nov 24, 2017

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