Abstract
At the application level, it is important to be able to define, around the measurement result, an interval which will contain an important part of the distribution of the measured values, that is, a confidence interval. This practice, which is acknowledged by the ISO Guide, is a major shift from the probabilistic representation as a confidence interval represents a set of possible values for a parameter associated with a confidence level. It can be considered as a probability-possibility transformation by viewing possibility distribution as encoding confidence intervals. In this paper, we extend previous works concerning the possibility expression of measurement uncertainty applied to situations where only very limited knowledge is available: one single measurement and unknown unimodal probability density
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