Tendency hypotheses – T-hypotheses, for short –, such as “the
individuals of the kind Y tend to be X”, are used within several empirical
sciences and play an important role in some of them, for instance in
social sciences. However, so far T-hypotheses have received little or no
attention by philosophers of science and statisticians.1 An exception is the
work made in the seventies of the past century by the statisticians and
social scientists David K. Hildebrand, James D. Laing, and Howard
Rosenthal who worked out – under the label of prediction logic –, an
interesting approach to the analysis of T-hypotheses.2
In this paper our main goal is the introduction of appropriate measures
for the verisimilitude of T-hypotheses.3 Our verisimilitude measures will
be defined in terms of the feature contrast (FC-) measures of similarity
proposed by the cognitive scientist Amos Tverski (1977). We shall
proceed as follows. In Section 1, Tverski’s FC-measures of similarity for
binary features are illustrated and suitably extended to quantitative
features. Afterwards, such measures are applied in the definition of
appropriate measures for the verisimilitude of universal and statistical
hypotheses (Section 2) and T-hypotheses (Section 3).
