Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry
Autor(a) principal: | |
---|---|
Data de Publicação: | 2007 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Chemical Society (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532007000200027 |
Resumo: | Least squares linear regression is widely used in analytical chemistry. In practice a linear relationship between substance content and measured value still has been assumed based on the correlation coefficient criterion, although not recommended. Textbooks provide the necessary formulas for the fitting process, based on the assumption that there is no error in the independent variable. In practice the ordinary least squares (OLS) textbook procedure is used even when the previously stated assumptions are not strictly fulfilled. In this paper, how to validate the calibration function is dealt with in detail using as an example based on measurements obtained for nickel determination by flame atomic absorption spectrometry (FAAS). Assessing uncertainties related to linear calibration curves is also discussed. Considering uncertainties of weights and volumetric equipment and instrumental analytical signal it is observed that the most important factor that contributes to the final uncertainty is the uncertainty of the calibration function. |
id |
SBQ-2_0bbff46b8a5e3d22ecd58ce1aa112c53 |
---|---|
oai_identifier_str |
oai:scielo:S0103-50532007000200027 |
network_acronym_str |
SBQ-2 |
network_name_str |
Journal of the Brazilian Chemical Society (Online) |
repository_id_str |
|
spelling |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometrymetrologyuncertaintycalibration functionflame atomic absorption spectrometryLeast squares linear regression is widely used in analytical chemistry. In practice a linear relationship between substance content and measured value still has been assumed based on the correlation coefficient criterion, although not recommended. Textbooks provide the necessary formulas for the fitting process, based on the assumption that there is no error in the independent variable. In practice the ordinary least squares (OLS) textbook procedure is used even when the previously stated assumptions are not strictly fulfilled. In this paper, how to validate the calibration function is dealt with in detail using as an example based on measurements obtained for nickel determination by flame atomic absorption spectrometry (FAAS). Assessing uncertainties related to linear calibration curves is also discussed. Considering uncertainties of weights and volumetric equipment and instrumental analytical signal it is observed that the most important factor that contributes to the final uncertainty is the uncertainty of the calibration function.Sociedade Brasileira de Química2007-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532007000200027Journal of the Brazilian Chemical Society v.18 n.2 2007reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.1590/S0103-50532007000200027info:eu-repo/semantics/openAccessChui,Queenie S. H.eng2007-06-13T00:00:00Zoai:scielo:S0103-50532007000200027Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2007-06-13T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
title |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
spellingShingle |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry Chui,Queenie S. H. metrology uncertainty calibration function flame atomic absorption spectrometry |
title_short |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
title_full |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
title_fullStr |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
title_full_unstemmed |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
title_sort |
Uncertainties related to linear calibration curves: a case study for flame atomic absorption spectrometry |
author |
Chui,Queenie S. H. |
author_facet |
Chui,Queenie S. H. |
author_role |
author |
dc.contributor.author.fl_str_mv |
Chui,Queenie S. H. |
dc.subject.por.fl_str_mv |
metrology uncertainty calibration function flame atomic absorption spectrometry |
topic |
metrology uncertainty calibration function flame atomic absorption spectrometry |
description |
Least squares linear regression is widely used in analytical chemistry. In practice a linear relationship between substance content and measured value still has been assumed based on the correlation coefficient criterion, although not recommended. Textbooks provide the necessary formulas for the fitting process, based on the assumption that there is no error in the independent variable. In practice the ordinary least squares (OLS) textbook procedure is used even when the previously stated assumptions are not strictly fulfilled. In this paper, how to validate the calibration function is dealt with in detail using as an example based on measurements obtained for nickel determination by flame atomic absorption spectrometry (FAAS). Assessing uncertainties related to linear calibration curves is also discussed. Considering uncertainties of weights and volumetric equipment and instrumental analytical signal it is observed that the most important factor that contributes to the final uncertainty is the uncertainty of the calibration function. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-04-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532007000200027 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532007000200027 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-50532007000200027 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Journal of the Brazilian Chemical Society v.18 n.2 2007 reponame:Journal of the Brazilian Chemical Society (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Journal of the Brazilian Chemical Society (Online) |
collection |
Journal of the Brazilian Chemical Society (Online) |
repository.name.fl_str_mv |
Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
||office@jbcs.sbq.org.br |
_version_ |
1750318167832395776 |