Estimation of the standard uncertainty of a calibration curve: Application to sulfur mass concentration determination in fuels

Theodorou, D; Zannikou, Y; Zannikos, F

dc.contributor.author	Theodorou, D	en
dc.contributor.author	Zannikou, Y	en
dc.contributor.author	Zannikos, F	en
dc.date.accessioned	2014-03-01T11:46:59Z
dc.date.available	2014-03-01T11:46:59Z
dc.date.issued	2012	en
dc.identifier.issn	09491775	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/38041
dc.subject	Calibration curve	en
dc.subject	Fuel	en
dc.subject	GUM	en
dc.subject	Monte Carlo method	en
dc.subject	Sulfur mass concentration	en
dc.subject	Uncertainty	en
dc.title	Estimation of the standard uncertainty of a calibration curve: Application to sulfur mass concentration determination in fuels	en
heal.type	other	en
heal.identifier.primary	10.1007/s00769-011-0852-4	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s00769-011-0852-4	en
heal.publicationDate	2012	en
heal.abstract	The construction of a calibration curve using least square linear regression is common in many analytical measurements, and it comprises an important uncertainty component of the whole analytical procedure uncertainty. In the present work, various methodologies are applied concerning the estimation of the standard uncertainty of a calibration curve used for the determination of sulfur mass concentration in fuels. The methodologies applied include the GUM uncertainty framework, the Kragten numerical method, the Monte Carlo method (MCM) as well as the approximate equation calculating the standard error of prediction. The standard uncertainty results obtained by all methodologies agree well (0.172-0.175 ng μL-1). Aspects of inappropriate use of the approximate equation of the standard error of prediction, which leads to overestimation or underestimation of calculated uncertainty, are discussed. Moreover, the importance of the correlation between calibration curve parameters (slope and intercept) within GUM, MCM and Kragten approaches is examined. © 2011 Springer-Verlag.	en
heal.journalName	Accreditation and Quality Assurance	en
dc.identifier.doi	10.1007/s00769-011-0852-4	en
dc.identifier.volume	17	en
dc.identifier.issue	3	en
dc.identifier.spage	275	en
dc.identifier.epage	281	en