• (1) JCGM 200:2008, International vocabularyof metrology — Basic and general concepts and associated terms (VIM), 3rd edition. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, 2008. Available on-line from http://www.bipm.org/en/publications/guides/vim.html

      (2) JCGM 100:2008 Evaluation of measurement data — Guide to the expression of uncertainty in measurement. JCGM, 2008. Available on-line from http://www.bipm.org/en/publications/guides/gum.html

      (3) Quantifying Uncertainty in Analytical Measurement, 2nd ed.; Ellison, S. L. R.; Williams, A., Eds.; EURACHEM/CITAC, 2012. Available on-line from http://eurachem.org/index.php/publications/guides 

      (4) Measurement Uncertainty Revisited. Eurolab Technical Report No 1/2007. Eurolab, 2007. Available on-line from http://www.eurolab.org/documents/1-2007.pdf 

      (5) Handbook for Calculation of Measurement Uncertainty in Environmental Laboratories. B. Magnusson, T. Näykki, H. Hovind, M. Krysell. Nordtest technical report 537, ed. 3. Nordtest, 2011. Available on-line from http://www.nordtest.info/index.php/technical-reports/ item/handbook-for-calculation-of-measurement-uncertainty-in-environmental-laboratories-nt-tr-537-edition-3.html 

      (6) Analytical Measurement: Measurement Uncertainty and Statistics. Eds: N. Majcen, V. Gegevicius. EC-JRC IRMM, 2012. Available on-line from http://publications.jrc.ec.europa.eu/repository/ bitstream/111111111/29537/1/lana2207enn-web.pdf

       

      L'utilisation pédagogique de MOOC a été décrite dans un article paru dans la revue Analytical and Bioanalytical Chemistry, 407 (2015) 1277-1281 "Using MOOCs for teaching analytical chemistry: experience at University of Tartu".


    • measurement accuracy / exactitude de mesure

      Accuracy

      Closeness of agreement between a measured quantity value and a true quantity value of a measurand

      NOTE 1 The concept ‘measurement accuracy’ is not a quantity and is not given a numerical quantity value. A measurement is said to be more accurate when it offers a smaller measurement error.

      NOTE 2 The term “measurement accuracy” should not be used for measurement trueness and the term “measurement precision” should not be used for ‘measurement accuracy’, which, however, is related to both these concepts.

      NOTE 3 ‘Measurement accuracy’ is sometimes understood as closeness of agreement between measured quantity values that are being attributed to the measurand.


      Exactitude

      Etroitesse de l'accord entre une valeur mesurée et une valeur vraie d'un mesurande

      NOTE 1 L'exactitude de mesure n'est pas une grandeur et ne s'exprime pas numériquement. Un mesurage est quelquefois dit plus exact s'il fournit une plus petite erreur de mesure.

      NOTE 2 Il convient de ne pas utiliser le terme «exactitude de mesure» pour la justesse de mesure et le terme «fidélité de mesure» pour l'exactitude de mesure. Celle-ci est toutefois liée aux concepts de justesse et de fidélité.

      NOTE 3 L'exactitude de mesure est quelquefois interprétée comme l'étroitesse de l'accord entre les valeurs mesurées qui sont attribuées au mesurande.


      measurement precision / fidélité de mesure

      Precision

      Closeness of agreement between indications or measured quantity values obtained by replicate measurements on the same or similar objects under specified conditions

      NOTE 1 Measurement precision is usually expressed numerically by measures of imprecision, such as standard deviation, variance, or coefficient of variation under the specified conditions of measurement.

      NOTE 2 The ‘specified conditions’ can be, for example, repeatability conditions of measurement, intermediate precision conditions of measurement, or reproducibility conditions of measurement (see ISO 5725-1:1994).

      NOTE 3 Measurement precision is used to define measurement repeatability, intermediate measurement precision, and measurement reproducibility.

      NOTE 4 Sometimes “measurement precision” is erroneously used to mean measurement accuracy. 


      Fidélité

      Etroitesse de l'accord entre les indications ou les valeurs mesurées obtenues par des mesurages répétés du même objet ou d'objets similaires dans des conditions spécifiées

      NOTE 1 La fidélité est en général exprimée numériquement par des caractéristiques telles que l'écart-type, la variance ou le coefficient de variation dans les conditions spécifiées.

      NOTE 2 Les conditions spécifiées peuvent être, par exemple, des conditions de répétabilité, des conditions de fidélité intermédiaire ou des conditions de reproductibilité (voir l'ISO 5725-1:1994).

      NOTE 3 La fidélité sert à définir la répétabilité de mesure, la fidélité intermédiaire de mesure et la reproductibilité de mesure.

      NOTE 4 Le terme «fidélité de mesure» est quelquefois utilisé improprement pour désigner l'exactitude de mesure.


      measurement trueness /justesse de mesure

      Trueness

      Closeness of agreement between the average of an infinite number of replicate measured quantity values and a reference quantity value

      NOTE 1 Measurement trueness is not a quantity and thus cannot be expressed numerically, but measures for closeness of agreement are given in ISO 5725.

      NOTE 2 Measurement trueness is inversely related to systematic measurement error, but is not related to random measurement error.

      NOTE 3 “Measurement accuracy” should not be used for ‘measurement trueness’.

      Justesse

      Etroitesse de l'accord entre la moyenne d'un nombre infini de valeurs mesurées répétées et une valeur de référence

      NOTE 1 La justesse de mesure n'est pas une grandeur et ne peut donc pas s'exprimer numériquement, mais l'ISO 5725 donne des caractéristiques pour l'étroitesse de l'accord.

      NOTE 2 La justesse de mesure varie en sens inverse de l'erreur systématique mais n'est pas liée à l'erreur aléatoire.

      NOTE 3 Il convient de ne pas utiliser «exactitude de mesure» pour la justesse de mesure.


    • https://uncertainty.nist.gov/

      The NIST Uncertainty Machine is a web-based software application produced by the National Institute of Standards and Technology (NIST) to evaluate the measurement uncertainty associated with a scalar or vectorial output quantity that is a known and explicit function of a set of scalar input quantities for which estimates and evaluations of measurement uncertainty are available.

      The NIST Uncertainty Machine implements the approximate method of uncertainty evaluation described in the "Guide to the expression of uncertainty in measurement" (GUM), and the Monte Carlo method of the GUM Supplements 1 and 2. Input and output quantities are modeled as random variables, and their probability distributions are used to characterize measurement uncertainty. For inputs that are correlated, the NIST Uncertainty Machine offers the means to specify the corresponding correlations, and the manner in which they will be taken into account.

      The output of the NIST Uncertainty Machine comprises:

      • An estimate of the output quantity (measurand)
      • Evaluations of the associated standard and expanded uncertainties
      • Coverage intervals for the true value of the measurand
      • An uncertainty budget that quantifies the influence that the uncertainties of the inputs have upon the uncertainty of the output

      For details about the NIST Uncertainty Machine, and examples of its application, please refer to its user's manual, and to T. Lafarge and A. Possolo (2015) "The NIST Uncertainty Machine", NCSLI Measure Journal of Measurement Science, volume 10, number 3 (September), pages 20-27.

      NIST is the national metrology institute of the United States of America. Visit us at www.nist.gov. Founded in 1901, NIST is a non-regulatory federal agency within the U.S. Department of Commerce. NIST's mission is to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life.

      Bug reports and suggestions for improvement are most welcome: please send them to antonio.possolo@nist.gov.

      Instructions

      • Select the number of input quantities.
      • Change the quantity names if necessary.
      • For each input quantity choose its distribution and its parameters.
      • Choose and set the correlations if necessary.
      • Choose the number of realizations.
      • Write the definition of the output quantity in a valid R expression.
      • Run the computation.