Using mobile-device sensors to teach students error analysis
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.
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) |
_version_ | 1807522796321898496 |
---|---|
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 |
id | COLIBRI_1e0490e5ea46ba4936319927434630a3 |
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 |
language_invalid_str_mv | en |
network_acronym_str | COLIBRI |
network_name_str | COLIBRI |
oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/38120 |
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 |