Standard Practice for Determining and Expressing Precision of Measurement Results, in the Analysis of Water, as Relative Standard Deviation, Utilizing DQCALC Software

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1.1 This practice describes a procedure for developing a graphical model of relative standard deviation versus concentration for analytical methods used in the analysis of water (methods that are subject to non-additive random errors) for the purpose of assigning a statement of noise or randomness to analytical results (commonly referred to as a precision statement), in either a manual or an automated fashion.  
1.2 Data analysis and modeling is done with Committee D19 Adjunct DQCALC2 (a Microsoft Excel3-based tool).  
1.3 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.  
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

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ASTM D7729-12(2018)e1 - Standard Practice for Determining and Expressing Precision of Measurement Results, in the Analysis of Water, as Relative Standard Deviation, Utilizing DQCALC Software
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This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the
Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
´1
Designation: D7729 − 12 (Reapproved 2018)
Standard Practice for
Determining and Expressing Precision of Measurement
Results, in the Analysis of Water, as Relative Standard
Deviation, Utilizing DQCALC Software
This standard is issued under the fixed designation D7729; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
ε NOTE—The Keywords section was added editorially in August 2018.
1. Scope measurement results are unable to determine if the data are
sufficiently precise for any specific data use.
1.1 This practice describes a procedure for developing a
graphical model of relative standard deviation versus concen-
2.2 Measurement uncertainty (MU) is most generally un-
tration for analytical methods used in the analysis of water
derstoodtobe“aparametercharacterizingthedispersionofthe
(methodsthataresubjecttonon-additiverandomerrors)forthe
quantity values being attributed to a measurand” (from VIM
purpose of assigning a statement of noise or randomness to
2.26). This definition can be implemented as an expression
analytical results (commonly referred to as a precision
(“uncertainty statement”) associated with an reported measure-
statement), in either a manual or an automated fashion.
ment that represents the statistically based (Type A estimate)
dispersion of experimental results around a reported value.
1.2 Data analysis and modeling is done with Committee
2 3
D19 Adjunct DQCALC (a Microsoft Excel -based tool).
2.3 There is no universally agreed upon format or nomen-
clature for uncertainty statements. The literature offers sugges-
1.3 The values stated in SI units are to be regarded as
tions ranging from simple expressions of standard deviation or
standard. No other units of measurement are included in this
“fractional uncertainty” (standard deviation divided by re-
standard.
ported result) to confidence intervals to detailed “uncertainty
1.4 This standard does not purport to address all of the
reports.”
safety concerns, if any, associated with its use. It is the
responsibility of the user of this standard to establish appro-
2.4 In addition to the “random” errors encompassed in the
priate safety, health, and environmental practices and deter-
ideas expressed in 1.1 and 1.2, there are also “systematic”
mine the applicability of regulatory limitations prior to use.
errors,biases,thatcanbeconsideredaspartofuncertainty.The
1.5 This international standard was developed in accor-
literature is not consistent on how unknown bias is considered
dance with internationally recognized principles on standard-
in an uncertainty statement. For purposes of this practice, bias
ization established in the Decision on Principles for the
is assumed to have been corrected for or insignificant in the
Development of International Standards, Guides and Recom-
reported results, and bias is not specifically incorporated in the
mendations issued by the World Trade Organization Technical
proposed uncertainty statement.
Barriers to Trade (TBT) Committee.
2.5 For purposes of this practice, the terms MU, uncertainty
statement,or measurement uncertainty will be used synony-
2. Introduction
mously to designate the expression accompanying measure-
2.1 An understanding of the uncertainty associated with
ment results for the purpose of assessing the utility of those
measurement results is necessary for evaluating the utility of
results.
those results. Without a reported uncertainty estimate, users of
2.6 This practice proposes the use of fractional uncertainty
or relative standard deviation (RSD) as the expression of MU.
This practice is under the jurisdiction ofASTM Committee D19 on Water and
2.7 Traditionally, in the generation and publication of data
is the direct responsibility of Subcommittee D19.02 on Quality Systems,
related to the analysis of water, a continuous function (model)
Specification, and Statistics.
describing the relationship of uncertainty (as standard devia-
Current edition approved Aug. 1, 2018. Published September 2018. Originally
approved in 2012. Last previous edition approved in 2012 as D7729 – 12. DOI:
tion) to concentration is not available. To compensate for this
10.1520/D7729-12R18E01.
lack, discrete points bounding certain levels of uncertainty are
Available fromASTM International Headquarters. OrderAdjunct No. ADJDQ-
calculated, for example, “detection limits” (typically around
CALC. Original adjunct produced in 2007.
Microsoft Excel is a trademark of the Microsoft Corporation, Redmond, WA. 33 % RSD) and “quantitation limits” (often around 10 %
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
´1
D7729 − 12 (2018)
RSD). Results are flagged to indicate their relationship to one reported determination, expressed as the relative standard
of these limits. Alternatively, this practice directs the creation deviation of typical measurements of the same form.
of a model of uncertainty (RSD versus concentration) which
4.3 Symbols:
allows assignment of a discrete uncertainty estimate to any
4.3.1 IQE—Inter-Laboratory Quantitation Estimate
result value measured within the range of modeled data.
4.3.2 LIMS—Laboratory Information Management System
2.8 This practice is based on the use of the DQCALC
4.3.3 MU—Measurement Uncertainty
software that was developed to simplify the calculation of the
4.3.4 RSD—Relative Standard Deviation
inter-laboratory quantitation estimate (IQE) (Practice D6512).
This practice is restricted to the development of an uncertainty
5. Summary of Practice
model for the reporting of MU within a single laboratory. In
additiontoprovidinganestimateofsingle-laboratorymeasure-
5.1 Therelationshipbetweenrelativestandarddeviationand
ment uncertainty, the DQCALC software automatically calcu-
concentration is modeled using a multi-replicate and multi-
lates L – from Curie, equivalent to the United States Envi-
level design and utilizing the curve fitting tools in the DQ-
C
ronmental Protection Agency (EPA)’s method detection limit
CALC software. The DQCALC software will return the
(MDL), and theASTM detection estimate for a single lab (this
coefficients for the selected function/model of standard devia-
utilizes a “3 sigma” tolerance interval rather than the standard
tion against concentration. The general equations are given in
confidence interval).
this practice. From the equation, the appropriate standard
deviation for any concentration in the range represented in the
2.9 This practice provides the tools to allow a laboratory to
model study can be calculated.This can then be converted into
embed the RSD versus concentration relationship into a
RSD, the recommended reporting format.
sufficiently powerful laboratory information management sys-
tem (LIMS) resulting in the ability to automatically report MU
5.2 PracticeD6512,theIQEpracticethatformsthebasisfor
with all data reported out of the LIMS for modeled parameters.
this practice, has the feature of correcting for recovery.
Therefore, for purposes of this practice, true concentrations,
2.10 The DQCALC software is available from ASTM (see
that is, concentrations that have been “corrected” for recovery
Practice D7510 and Adjunct DQCALC ).
bias are used. Where a laboratory in use of its methods of
2.11 In addition, this practice discusses the variables that
testing does not correct resultant values, the calculated RSD
should be considered for inclusion in the uncertainty modeling
will be marginally higher or lower, depending on the magni-
study.
tude of the uncorrected bias in the reported data. Where
uncorrected bias is less than 10 % of the magnitude of the
3. Referenced Documents
result, the error in the RSD estimate may be considered
3.1 ASTM Standards:
insignificant.
D1129 Terminology Relating to Water
D6512 Practice for Interlaboratory Quantitation Estimate
6. Sources of Imprecision
D7510 Practice for Performing Detection and Quantitation
6.1 When utilizing the result of a measurement to make a
Estimation and Data Assessment Utilizing DQCALC
binarydecision(yes/no,pass/fail,etc.)thereisariskofmaking
Software, based onASTM Practices D6091 and D6512 of
a false positive determination (saying a condition exists when
Committee D19 on Water
5 it does not) or a false negative determination (saying a
3.2 Other Documents:
condition does not exist when it does). The more precise the
VIM InternationalVocabulary of Metrology, Basic and Gen-
estimate of the measurement uncertainty of the result (the
eral Concepts and Associated Terms, 3rd edition, JCGM
smaller the relative standard deviation), the less chance there is
200:2008
of making such incorrect assessments.
4. Terminology
6.2 The most precise possible estimate of a result’s MU
would be obtained through replicate measurements done at the
4.1 Definitions:
same time as the initial measurement. (This would, of course,
4.1.1 For definitions of terms used in this standard, refer to
also give a more precise estimate of the measurement result –
Terminology D1129.
a mean with n > 1). The greater the number of replicates
4.2 Definitions of Terms Specific to This Standard:
performed,thebettertheestimateofMU.Inpractice,thislevel
4.2.1 measurement uncertainty, n—in the analysis of water,
of analytical work is rarely performed, unless there are dire
a value representing the precision of a reported determination.
consequences associated with the result.
4.2.2 water analysis measurement uncertainty, n—in the
6.3 Under typical circumstances in analytical laboratories,
analysis of water, a value representing the precision of a
uncertainty is not determined from replicates of real-world
samples. An assumption (rarely tested) is made that the
uncertainty of the measurements of standards of known (trace-
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
able) concentration is comparable to the uncertainty of mea-
Standards volum
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