 A terminological note: With a “variable” \(X\) (in the mathematical sense) we mean a functional property of individuals \(d\in D\) of a domain \(D\), i.e., a function \(X: D\rightarrow \ran(X)\) from \(D\) into \(\ran(X)\). The set \(\ran(X)\) (for “range of \(X\)”) is the set of possible values \(x\in\ran(X)\) of the variable \(X\); if \(X\) is quantitative, \(\ran(X) = \Re\), i.e., the set of real numbers. (If \(ran(X) = \Re\) and the values of \(X\) are distributed according to a given probability distribution, then \(X\) is what is called a ‘random variable’ in probability theory; cf. Hays and Winkler 1975). In what follows, “\(d_{(i)}\)” denotes proper individual variables (in the logical sense) and “\(x_{(i)}\)” denotes possible values of functional variables \(X_{(i)}\). An important subcase of comparative cp-laws are probabilistic comparative cp-laws, in which the quantitative variables \(X\) express the probabilities \(P(F)\) of some qualitative properties expressed by predicates \(F\) (for instance, \(F\) might be the increased probability of a car accident in example (2) below).