Abstract
Since real-life measurements cannot be absolutely precise, we never know the precise value of a physical quantity, we only know an interval of its possible values. Due to this uncertainty, there are several different models that are consistent with the same measurement results. Which model should we choose? In this paper, we show that Ockham's razor principle (Entities should not be multiplied unnecessarily) can lead to a natural criterion for choosing a model. As an example, we apply this criterion to data processing related to a reasonably simple psychological problem.
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