A correlation between two sets of observations does not necessarily indicate a causative relationship between the two measured characteristics. It is often the case that X and Y are correlated because both are related to Z, and neither X nor Y influence the other. For example, rainfall on a given day is highly correlated with rainfall on the preceding day, but this does not reflect a causative relationship so much as a tendency for weather patterns to persist for several days. When designing experiments that search for causative relationships, one must consider alternate relationships that will produce correlations like this one.