Using mobile-device sensors to teach students error analysis

Monteiro, Martín - Stari, Cecilia - Cabeza, Cecilia - Martí, Arturo

Resumen:

Science students must deal with the errors inherent to all physical measurements and be conscious of the need to expressvthem as a best estimate and a range of uncertainty. Errors are routinely classified as statistical or systematic. Although statistical errors are usually dealt with in the first years of science studies, the typical approaches are based on manually performing repetitive observations. Our work proposes a set of laboratory experiments to teach error and uncertainties based on data recorded with the sensors available in many mobile devices. The main aspects addressed are the physical meaning of the mean value and standard deviation, and the interpretation of histograms and distributions. The normality of the fluctuations is analyzed qualitatively comparing histograms with normal curves and quantitatively comparing the number of observations in intervals to the number expected according to a normal distribution and also performing a Chi-squared test. We show that the distribution usually follows a normal distribution, however, when the sensor is placed on top of a loudspeaker playing a pure tone significant differences with a normal distribution are observed. As applications to every day situations we discuss the intensity of the fluctuations in different situations, such as placing the device on a table or holding it with the hands in different ways. Other activities are focused on the smoothness of a road quantified in terms of the fluctuations registered by the accelerometer. The present proposal contributes to gaining a deep insight into modern technologies and statistical errors and, finally, motivating and encouraging engineering and science students.


Detalles Bibliográficos
2020
PEDECIBA: Fisica Nolineal (ID 722)
Ferromagnetic materials
Magnetic equipment
Acoustic transducers
Measuring instruments
Laboratory procedures
Sensors
Engineering science
Students
Teaching
Gaussian processes
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/38120
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Monteiro, Martín
author2 Stari, Cecilia
Cabeza, Cecilia
Martí, Arturo
author2_role author
author
author
author_facet Monteiro, Martín
Stari, Cecilia
Cabeza, Cecilia
Martí, Arturo
author_role author
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collection COLIBRI
dc.contributor.filiacion.none.fl_str_mv Monteiro Martín, Universidad ORT (Uruguay)
Stari Cecilia, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.
Cabeza Cecilia, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.
Martí Arturo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.
dc.creator.none.fl_str_mv Monteiro, Martín
Stari, Cecilia
Cabeza, Cecilia
Martí, Arturo
dc.date.accessioned.none.fl_str_mv 2023-07-13T13:11:35Z
dc.date.available.none.fl_str_mv 2023-07-13T13:11:35Z
dc.date.issued.none.fl_str_mv 2020
dc.description.abstract.none.fl_txt_mv Science students must deal with the errors inherent to all physical measurements and be conscious of the need to expressvthem as a best estimate and a range of uncertainty. Errors are routinely classified as statistical or systematic. Although statistical errors are usually dealt with in the first years of science studies, the typical approaches are based on manually performing repetitive observations. Our work proposes a set of laboratory experiments to teach error and uncertainties based on data recorded with the sensors available in many mobile devices. The main aspects addressed are the physical meaning of the mean value and standard deviation, and the interpretation of histograms and distributions. The normality of the fluctuations is analyzed qualitatively comparing histograms with normal curves and quantitatively comparing the number of observations in intervals to the number expected according to a normal distribution and also performing a Chi-squared test. We show that the distribution usually follows a normal distribution, however, when the sensor is placed on top of a loudspeaker playing a pure tone significant differences with a normal distribution are observed. As applications to every day situations we discuss the intensity of the fluctuations in different situations, such as placing the device on a table or holding it with the hands in different ways. Other activities are focused on the smoothness of a road quantified in terms of the fluctuations registered by the accelerometer. The present proposal contributes to gaining a deep insight into modern technologies and statistical errors and, finally, motivating and encouraging engineering and science students.
dc.description.es.fl_txt_mv Publicado también como: American Journal of Physics, 2021, 89(5): 477–481. DOI: 10.1119/10.0002906
dc.description.sponsorship.none.fl_txt_mv PEDECIBA: Fisica Nolineal (ID 722)
dc.format.extent.es.fl_str_mv 15 h
dc.format.mimetype.es.fl_str_mv application/pdf
dc.identifier.citation.es.fl_str_mv Monteiro, M, Stari, C, Cabeza, C [y otro autor]. "Using mobile-device sensors to teach students error analysis". [Preprint]. Publicado en: Physics (Physics Education). 2020, arXiv:2009.07049, sep 2020, pp 1-15.
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/38120
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv arXiv
dc.relation.ispartof.es.fl_str_mv Physics (Physics Education), arXiv:2009.07049, sep 2020, pp 1-15
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Ferromagnetic materials
Magnetic equipment
Acoustic transducers
Measuring instruments
Laboratory procedures
Sensors
Engineering science
Students
Teaching
Gaussian processes
dc.title.none.fl_str_mv Using mobile-device sensors to teach students error analysis
dc.type.es.fl_str_mv Preprint
dc.type.none.fl_str_mv info:eu-repo/semantics/preprint
dc.type.version.none.fl_str_mv info:eu-repo/semantics/submittedVersion
description Publicado también como: American Journal of Physics, 2021, 89(5): 477–481. DOI: 10.1119/10.0002906
eu_rights_str_mv openAccess
format preprint
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identifier_str_mv Monteiro, M, Stari, C, Cabeza, C [y otro autor]. "Using mobile-device sensors to teach students error analysis". [Preprint]. Publicado en: Physics (Physics Education). 2020, arXiv:2009.07049, sep 2020, pp 1-15.
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
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network_acronym_str COLIBRI
network_name_str COLIBRI
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publishDate 2020
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling Monteiro Martín, Universidad ORT (Uruguay)Stari Cecilia, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.Cabeza Cecilia, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.Martí Arturo, Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Física.2023-07-13T13:11:35Z2023-07-13T13:11:35Z2020Monteiro, M, Stari, C, Cabeza, C [y otro autor]. "Using mobile-device sensors to teach students error analysis". [Preprint]. Publicado en: Physics (Physics Education). 2020, arXiv:2009.07049, sep 2020, pp 1-15.https://hdl.handle.net/20.500.12008/38120Publicado también como: American Journal of Physics, 2021, 89(5): 477–481. DOI: 10.1119/10.0002906Science students must deal with the errors inherent to all physical measurements and be conscious of the need to expressvthem as a best estimate and a range of uncertainty. Errors are routinely classified as statistical or systematic. Although statistical errors are usually dealt with in the first years of science studies, the typical approaches are based on manually performing repetitive observations. Our work proposes a set of laboratory experiments to teach error and uncertainties based on data recorded with the sensors available in many mobile devices. The main aspects addressed are the physical meaning of the mean value and standard deviation, and the interpretation of histograms and distributions. The normality of the fluctuations is analyzed qualitatively comparing histograms with normal curves and quantitatively comparing the number of observations in intervals to the number expected according to a normal distribution and also performing a Chi-squared test. We show that the distribution usually follows a normal distribution, however, when the sensor is placed on top of a loudspeaker playing a pure tone significant differences with a normal distribution are observed. As applications to every day situations we discuss the intensity of the fluctuations in different situations, such as placing the device on a table or holding it with the hands in different ways. Other activities are focused on the smoothness of a road quantified in terms of the fluctuations registered by the accelerometer. The present proposal contributes to gaining a deep insight into modern technologies and statistical errors and, finally, motivating and encouraging engineering and science students.Submitted by Faget Cecilia (lfaget@fcien.edu.uy) on 2023-07-13T11:34:08Z No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) 2009.07049.pdf: 2763065 bytes, checksum: 131f1d82bc6fef58d7adb3ebd2bce0eb (MD5)Approved for entry into archive by Faget Cecilia (lfaget@fcien.edu.uy) on 2023-07-13T11:37:12Z (GMT) No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) 2009.07049.pdf: 2763065 bytes, checksum: 131f1d82bc6fef58d7adb3ebd2bce0eb (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@seciu.edu.uy) on 2023-07-13T13:11:35Z (GMT). No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) 2009.07049.pdf: 2763065 bytes, checksum: 131f1d82bc6fef58d7adb3ebd2bce0eb (MD5) Previous issue date: 2020PEDECIBA: Fisica Nolineal (ID 722)15 happlication/pdfenengarXivPhysics (Physics Education), arXiv:2009.07049, sep 2020, pp 1-15Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. 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spellingShingle Using mobile-device sensors to teach students error analysis
Monteiro, Martín
Ferromagnetic materials
Magnetic equipment
Acoustic transducers
Measuring instruments
Laboratory procedures
Sensors
Engineering science
Students
Teaching
Gaussian processes
status_str submittedVersion
title Using mobile-device sensors to teach students error analysis
title_full Using mobile-device sensors to teach students error analysis
title_fullStr Using mobile-device sensors to teach students error analysis
title_full_unstemmed Using mobile-device sensors to teach students error analysis
title_short Using mobile-device sensors to teach students error analysis
title_sort Using mobile-device sensors to teach students error analysis
topic Ferromagnetic materials
Magnetic equipment
Acoustic transducers
Measuring instruments
Laboratory procedures
Sensors
Engineering science
Students
Teaching
Gaussian processes
url https://hdl.handle.net/20.500.12008/38120