There are two well-known and different approaches to statistical inference and hypothesis testing, i.e. the frequentist (or orthodox) and the Bayesian one. Consequently, there are also (if one stays in the framework of probability theory) two rival approaches to uncertainty. The present work is partly a tutorial, aimed at explaining the basic aspects of the two approaches, and their relationship with the GUM; and partly a demonstration that the implementation of the Bayesian approach in the GUM Supplement 1 is too rigid. In particular, objective Bayesianism is incompatible with the propagation of distributions prescribed in Supplement 1.

About the Frequentist and the Bayesian Approach to Uncertainty

Nicola Giaquinto;Laura Fabbiano;Amerigo Trotta;Gaetano Vacca
2014-01-01

Abstract

There are two well-known and different approaches to statistical inference and hypothesis testing, i.e. the frequentist (or orthodox) and the Bayesian one. Consequently, there are also (if one stays in the framework of probability theory) two rival approaches to uncertainty. The present work is partly a tutorial, aimed at explaining the basic aspects of the two approaches, and their relationship with the GUM; and partly a demonstration that the implementation of the Bayesian approach in the GUM Supplement 1 is too rigid. In particular, objective Bayesianism is incompatible with the propagation of distributions prescribed in Supplement 1.
2014
20th IMEKO T4 International Symposium and 18th IWADC Workshop Advances in Instrumentation and Sensors Interoperability
978-92-990073-2-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/16368
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