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Statistical analysis for explosives detection system test and evaluation
The verification of trace explosives detection systems is often constrained to small sample sets, so it is important to support the significance of the results with statistical analysis. As binary measurements, the trials are assessed using binomial statistics. A method is described based on the pro...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742070/ https://www.ncbi.nlm.nih.gov/pubmed/34996947 http://dx.doi.org/10.1038/s41598-021-03755-1 |
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author | Lukow, Stefan Weatherall, James C. |
author_facet | Lukow, Stefan Weatherall, James C. |
author_sort | Lukow, Stefan |
collection | PubMed |
description | The verification of trace explosives detection systems is often constrained to small sample sets, so it is important to support the significance of the results with statistical analysis. As binary measurements, the trials are assessed using binomial statistics. A method is described based on the probability confidence interval and expressed in terms of the upper confidence interval bound that reports the probability of successful detection and its level of statistical confidence. These parameters provide useful measures of the system’s performance. The propriety of combining statistics for similar tests—for example in trace detection trials of an explosive on multiple surfaces—is examined by statistical tests. The use of normal statistics is commonly applied to binary testing, but the confidence intervals are known to behave poorly in many circumstances, including small sample numbers. The improvement of the normal approximation with increasing sample number is shown not to be substantial for the typical numbers used in this type of explosives detection system testing, and binary statistics are preferred. The methods and techniques described here for testing trace detection can be applied as well to performance testing of explosives detection systems in general. |
format | Online Article Text |
id | pubmed-8742070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87420702022-01-11 Statistical analysis for explosives detection system test and evaluation Lukow, Stefan Weatherall, James C. Sci Rep Article The verification of trace explosives detection systems is often constrained to small sample sets, so it is important to support the significance of the results with statistical analysis. As binary measurements, the trials are assessed using binomial statistics. A method is described based on the probability confidence interval and expressed in terms of the upper confidence interval bound that reports the probability of successful detection and its level of statistical confidence. These parameters provide useful measures of the system’s performance. The propriety of combining statistics for similar tests—for example in trace detection trials of an explosive on multiple surfaces—is examined by statistical tests. The use of normal statistics is commonly applied to binary testing, but the confidence intervals are known to behave poorly in many circumstances, including small sample numbers. The improvement of the normal approximation with increasing sample number is shown not to be substantial for the typical numbers used in this type of explosives detection system testing, and binary statistics are preferred. The methods and techniques described here for testing trace detection can be applied as well to performance testing of explosives detection systems in general. Nature Publishing Group UK 2022-01-07 /pmc/articles/PMC8742070/ /pubmed/34996947 http://dx.doi.org/10.1038/s41598-021-03755-1 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lukow, Stefan Weatherall, James C. Statistical analysis for explosives detection system test and evaluation |
title | Statistical analysis for explosives detection system test and evaluation |
title_full | Statistical analysis for explosives detection system test and evaluation |
title_fullStr | Statistical analysis for explosives detection system test and evaluation |
title_full_unstemmed | Statistical analysis for explosives detection system test and evaluation |
title_short | Statistical analysis for explosives detection system test and evaluation |
title_sort | statistical analysis for explosives detection system test and evaluation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742070/ https://www.ncbi.nlm.nih.gov/pubmed/34996947 http://dx.doi.org/10.1038/s41598-021-03755-1 |
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