 According to the S-R model, in order to explain an event one must exhibit all the factors that are statistically relevant to its happening, without mentioning irrelevant elements, so that an explanatory account should include only information that is genuinely explanatory. In order to accomplish this task, the event explanandum must be referred to a homogeneous reference class, namely to the class containing all and only the relevant properties. Homogeneity is obtained through statistically relevant partitions of non-homogeneous reference classes into mutually exclusive and exhaustive sub-classes. Statistical relevance, providing the tool to attain homogeneity, is defined as follows. Let A stand for the reference class including some event of which one wants to establish the probability of possessing the property B; \(p (B \mid A)\) be the probability of B within the reference class A, and C be another property by which the class A can be divided into two sub-classes \((A \amp C)\) and \((A \amp \msim C)\); the property C is statistically relevant with respect to B in A if and only if \(p (B \amp C \mid A) \ne p (B \mid A)\). A homogeneous partition of a reference class does not admit further relevant partitions, and the resulting sub-classes must be maximal, in the sense that no irrelevant properties are retained.