| Zugriffsnummer | 25489 |
| Dokumenttyp | Konferenzartikel |
| Sprache | Englisch |
| Titel | A more general type A evaluation |
| Autor(in); Institution |
Kessel, Rüdiger; National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
Knacker, Raghu; National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
Sommer, Klaus-Dieter; 3, Chemische Physik und Explosionsschutz, PTB-Braunschweig
|
| Quelle/Jahr | Proceedings of the 10th ISMQC, the 10th International Symposium on Measurement and Quality Control:(2010), F3-035-1 - F3-035-6 |
| Availability | [CD-ROM] paper no.35 |
| Herausgeber(in) |
Takaya, Y.
|
| ISBN | 978-4-9905119-0-6 |
| Verlag | Tokyo: JSPE Techn. Committee for Intelligent Nano-Measure |
| Konferenzangaben | 10th International Symposium on Measurement and Quality Control (ISMQC-2010), Osaka, 05-09, September, 2010, Japan |
| Freie Schlagworte | Uncertainty evaluation ; Type A uncertainty ; Non Gaussian Observartion process |
| Zusammenfassung | The evaluation of uncertainty according to the Guide to the Expression of Uncertainty in measurement is the internationally agreed procedure to evaluate the complete result statement in measurement uncluding measurement uncertainty. It distinguishes two types of evaluation: Type A and Type B. With the publication of the Supplement 1 to the GUM another method to calculated the result with uncertainty is available to the scientific community. In this paper we discuss the concepts behind the evaluation of Type A in the original GUM an in its supplement and the differences in the results. Metrology and test laboratories are often unable to collect a large numer of sample values for the the observed quantities in the uncertainty budget. In addition, often the knowledge about the statistical properties of the obersvation process is limited. Therefore better guidance is needed on how to find a proper standard uncertainty when the number of observations is small ((10) or the observed process cannot be characterized as being normal. We analyze the problem of sampling from non-Gaussian observation processes. We simulate different observation processes and analyze the properties of small samples from these processes. Based on our finding we propose a more general approach to Type A evaluation. |
