 Lewis rejected the view that probabilities are empirically based estimates of the limiting value of the frequency of instances of a property in a population, and thus expressed in non-terminating judgments. First, he thought that any attempt to define probabilities as the ratio of instances of one property among instances of another property as the latter approaches infinity would make probability judgments empirically untestable. Second, he argued that, if probability judgements were empirical frequency claims, then the probability judgements would themselves only be probable, something that can’t be coherently accounted for. Nonetheless, Lewis recognized the need to assure ourselves rationally that the frequency as validly estimated from the data is closely in accord with the actual frequency and that there is nothing in the case at hand affecting the occurrence of the property which isn’t taken into account in the specification of the reference class. Lewis dubbed this the reliability of the determination of probability or expectation. He thought that reliability is a function of the adequacy of data (e.g. size of sample), the uniformity with which the frequency of some property in the data as a whole also holds for subsets of the data, and the proximateness or degree of resemblance of the case at hand in P to the data, all of which he also thought are logical relations.