Random-fuzzy variable: Difference between revisions

Revision as of 12:18, 5 July 2019

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{{Orphan|date=July 2019}}

In measurements, the measurement obtained can suffer from two types of uncertainties.<ref>{{Cite book|url=https://www.worldcat.org/oclc/34150960|title=An introduction to error analysis : the study of uncertainties in physical measurements|last=Taylor, John R. (John Robert), 1939-|date=1997|publisher=University Science Books|isbn=0935702423|edition= 2nd|___location=Sausalito, Calif.|oclc=34150960}}</ref> The first is the random uncertainty which is due to the noise in the process and the measurement. The second contribution is due to the systematic uncertainty which may be present in the measuring instrument. Systematic errors, if detected, can be easily compensated as they are usually constant throughout the measurement process as long as the measuring instrument and the measurement process are not changed. But it can not be accurately known while using the instrument if there is a [[systematic error]] and if there is, how much? Hence, systematic uncertainty could be considered as a contribution of a fuzzy nature.