Ignacio Lira and Wolfgang Wöger 2006 Metrologia 43 S249 doi:10.1088/0026-1394/43/4/S12
Ignacio Lira1,3 and Wolfgang Wöger2,4
Show affiliationsMeasurement data subject only to random effects can be evaluated within the frameworks of conventional as well as Bayesian statistical theory. In this paper, both viewpoints are presented and examples including Gaussian, uniform and Poisson statistics are discussed. The cases of data produced by different observers, and of quantities expressed by measurement models involving systematic effects, are also briefly touched upon. It is shown that, although in most practical cases the uncertainty intervals obtained from repeated measurements using either theory may be similar, their interpretation is completely different. Since the Bayesian approach treats random and systematic effects in the same way, the authors claim that it is more flexible and better adapted to practice than conventional theory.
02.50.Ng Distribution theory and Monte Carlo studies
Issue 4 (August 2006)
Received 15 November 2005
Published 4 August 2006
Ignacio Lira and Wolfgang Wöger 2006 Metrologia 43 S249
G Cavagnero et al 2004 Metrologia 41 445
Lijia Liu et al 2009 J. Phys.: Conf. Ser. 190 012134
Charles A Greenhall 2007 Metrologia 44 491
Rodolfo Gambini et al 2004 Class. Quantum Grav. 21 L51
David R Lapp 2003 Phys. Educ. 38 316
F Rodolakis et al 2009 J. Phys.: Conf. Ser. 190 012092
C I Pakes et al 2003 Nanotechnology 14 157
J Ulanski et al 1990 J. Phys. D: Appl. Phys. 23 75
Yuh-Ying Lin Wang et al 2004 Physiol. Meas. 25 1397