ABSTRACT
Aleatory uncertainty is related to a measurement random and systematic errors. Stochastic distortions distribution remain estimated and imprecise in respect to their types and parameters. Uncertainty also embraces subjective assessment of each piece of available data. In traditional approach there is no room for modelling and processing all mentioned items. Moreover results of observations, final outcome quality evaluation, can be evaluated a priori before taking measurements. A posteriori analyses is impaired, it is not embedded into the scheme of traditional way of inaccurate data handling. To introduce the new idea one should explore alternative approaches towards doubtfulness modelling. Presented rational starts with basic interval uncertainty model.
