“Probability theory is an ideal tool for formalizing uncertainty in situations where class frequencies are known or where evidence is based on outcomes of a sufficiently long series of independent random experiments. Possibility theory, on the other hand, is ideal for formalizing incomplete information expressed in terms of fuzzy propositions.”

—  George Klir

Source: Fuzzy sets and fuzzy logic (1995), p. 205 cited in: Flavio Comim, et al. (2008) The Capability Approach: Concepts, Measures and Applications. p. 298.

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George Klir 16
American computer scientist 1932–2016

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p 6
The Undiscovered Self (1958)
Context: Any theory based on experience is necessarily statistical; that is to say, it formulates an ideal average which abolishes all exceptions at either end of the scale and replaces them by an abstract mean. This mean is quite valid though it need not necessarily occur in reality. Despite this it figures in the theory as an unassailable fundamental fact. … If, for instance, I determine the weight of each stone in a bed of pebbles and get an average weight of 145 grams, this tells me very little about the real nature of the pebbles. Anyone who thought, on the basis of these findings, that he could pick up a pebbles of 145 grams at the first try would be in for a serious disappointment. Indeed, it might well happen that however long he searched he would not find a single pebble weighing exactly 145 grams. The statistical method shows the facts in the light of the ideal average but does not give us a picture of their empirical reality. While reflecting an indisputable aspect of reality, it can falsify the actual truth in a most misleading way.

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