 Some of the terms used in this deduction require explication. Two test situations are homogeneous on the condition that, if a factor is causally relevant and is present in test situation S1, then it is also present in test situation S2, and vice versa. A confounder would be a causally relevant factor that does not belong to the set {A, W}. The presence of such a confounder is excluded by the assumption of causal homogeneity (1). In practical situations, a confounder might be an unknown or uncontrolled (i.e., not measurable or not measured) factor that is present in only one of the test situations. In our antibiotics example, this could be some chemical that was put into just one aliquot inadvertently or without knowledge of the experimenter. In fact, the risk of a confounder is precisely why our biological experimenter will divide up the mother culture into aliquots just before putting in the substance to be tested. This makes it unlikely that one aliquot contains an uncontrolled chemical that the other does not contain. Furthermore, a skilled experimenter will make sure that the cultures are well stirred, thus preventing a physical-chemical inhomogeneity of the culture (e.g., some chemical or temperature gradient). Thus, there are typical laboratory manipulations and procedures that reduce the risk of confounders.