The reversed-axis method to estimate precision in standard additions analysis

Detalhes bibliográficos
Autor(a) principal: Goncalves, Daniel A. [UNESP]
Data de Publicação: 2016
Outros Autores: Jones, Bradley T., Donati, George L.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.microc.2015.08.006
http://hdl.handle.net/11449/167989
Resumo: The standard additions (SA) method is one of the most important calibration strategies in quantitative chemical analysis. It is a powerful tool to minimize matrix effects and enable precise and accurate determinations. On the other hand, the SA method is time-consuming and cumbersome because it requires the preparation of a calibration curve for each individual sample. Considering the statistical treatment required, the estimation of precision in SA determinations can be as laborious and cumbersome as the experimental procedure itself. In this work, we describe a simple method to quickly estimate standard deviations in SA analyses using the determination of Na and K in biodiesel by flame atomic emission spectrometry (FAES) as a model. By taking analyte concentration as the dependent variable (y-axis), and instrument response as the independent variable (x-axis), the standard deviation of the analyte concentration in the sample is equal to the error in the y-axis intercept of the SA calibration curve. This value can be easily calculated using a simple equation or the regression feature in MS Excel. Standard deviation values calculated using MS Excel and this reversed-axis method are compared to results from the traditional statistical methods of extrapolation and error propagation. In all determinations, the results from the extrapolation, error propagation with covariance, and reversed-axis methods are identical, which demonstrates their equivalence.
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spelling The reversed-axis method to estimate precision in standard additions analysisBiodieselCalibrationError propagationMS ExcelStandard additionsStandard deviationThe standard additions (SA) method is one of the most important calibration strategies in quantitative chemical analysis. It is a powerful tool to minimize matrix effects and enable precise and accurate determinations. On the other hand, the SA method is time-consuming and cumbersome because it requires the preparation of a calibration curve for each individual sample. Considering the statistical treatment required, the estimation of precision in SA determinations can be as laborious and cumbersome as the experimental procedure itself. In this work, we describe a simple method to quickly estimate standard deviations in SA analyses using the determination of Na and K in biodiesel by flame atomic emission spectrometry (FAES) as a model. By taking analyte concentration as the dependent variable (y-axis), and instrument response as the independent variable (x-axis), the standard deviation of the analyte concentration in the sample is equal to the error in the y-axis intercept of the SA calibration curve. This value can be easily calculated using a simple equation or the regression feature in MS Excel. Standard deviation values calculated using MS Excel and this reversed-axis method are compared to results from the traditional statistical methods of extrapolation and error propagation. In all determinations, the results from the extrapolation, error propagation with covariance, and reversed-axis methods are identical, which demonstrates their equivalence.Department of Physics and Chemistry UNESP-Univ Estadual PaulistaDepartment of Chemistry Wake Forest University, Salem Hall Box 7486Department of Physics and Chemistry UNESP-Univ Estadual PaulistaUniversidade Estadual Paulista (Unesp)Wake Forest UniversityGoncalves, Daniel A. [UNESP]Jones, Bradley T.Donati, George L.2018-12-11T16:39:09Z2018-12-11T16:39:09Z2016-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article155-158application/pdfhttp://dx.doi.org/10.1016/j.microc.2015.08.006Microchemical Journal, v. 124, p. 155-158.0026-265Xhttp://hdl.handle.net/11449/16798910.1016/j.microc.2015.08.0062-s2.0-849408512612-s2.0-84940851261.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMicrochemical Journalinfo:eu-repo/semantics/openAccess2023-10-13T06:05:44Zoai:repositorio.unesp.br:11449/167989Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-10-13T06:05:44Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv The reversed-axis method to estimate precision in standard additions analysis
title The reversed-axis method to estimate precision in standard additions analysis
spellingShingle The reversed-axis method to estimate precision in standard additions analysis
Goncalves, Daniel A. [UNESP]
Biodiesel
Calibration
Error propagation
MS Excel
Standard additions
Standard deviation
title_short The reversed-axis method to estimate precision in standard additions analysis
title_full The reversed-axis method to estimate precision in standard additions analysis
title_fullStr The reversed-axis method to estimate precision in standard additions analysis
title_full_unstemmed The reversed-axis method to estimate precision in standard additions analysis
title_sort The reversed-axis method to estimate precision in standard additions analysis
author Goncalves, Daniel A. [UNESP]
author_facet Goncalves, Daniel A. [UNESP]
Jones, Bradley T.
Donati, George L.
author_role author
author2 Jones, Bradley T.
Donati, George L.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Wake Forest University
dc.contributor.author.fl_str_mv Goncalves, Daniel A. [UNESP]
Jones, Bradley T.
Donati, George L.
dc.subject.por.fl_str_mv Biodiesel
Calibration
Error propagation
MS Excel
Standard additions
Standard deviation
topic Biodiesel
Calibration
Error propagation
MS Excel
Standard additions
Standard deviation
description The standard additions (SA) method is one of the most important calibration strategies in quantitative chemical analysis. It is a powerful tool to minimize matrix effects and enable precise and accurate determinations. On the other hand, the SA method is time-consuming and cumbersome because it requires the preparation of a calibration curve for each individual sample. Considering the statistical treatment required, the estimation of precision in SA determinations can be as laborious and cumbersome as the experimental procedure itself. In this work, we describe a simple method to quickly estimate standard deviations in SA analyses using the determination of Na and K in biodiesel by flame atomic emission spectrometry (FAES) as a model. By taking analyte concentration as the dependent variable (y-axis), and instrument response as the independent variable (x-axis), the standard deviation of the analyte concentration in the sample is equal to the error in the y-axis intercept of the SA calibration curve. This value can be easily calculated using a simple equation or the regression feature in MS Excel. Standard deviation values calculated using MS Excel and this reversed-axis method are compared to results from the traditional statistical methods of extrapolation and error propagation. In all determinations, the results from the extrapolation, error propagation with covariance, and reversed-axis methods are identical, which demonstrates their equivalence.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01
2018-12-11T16:39:09Z
2018-12-11T16:39:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.microc.2015.08.006
Microchemical Journal, v. 124, p. 155-158.
0026-265X
http://hdl.handle.net/11449/167989
10.1016/j.microc.2015.08.006
2-s2.0-84940851261
2-s2.0-84940851261.pdf
url http://dx.doi.org/10.1016/j.microc.2015.08.006
http://hdl.handle.net/11449/167989
identifier_str_mv Microchemical Journal, v. 124, p. 155-158.
0026-265X
10.1016/j.microc.2015.08.006
2-s2.0-84940851261
2-s2.0-84940851261.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Microchemical Journal
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 155-158
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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