When considering research results, what should one infer if relationships are correlated?

When relationships are correlated, it is important to recognize that correlation indicates a relationship between two variables but does not definitively establish that one causes the other. The correct inference is that causation may or may not be present. This means that while two variables may change together, it does not imply that one is responsible for the change in the other; there could be other factors involved, or the relationship could be coincidental.

For example, an observed correlation between the amount of ice cream sold and the incidence of sunburns might suggest a relationship; however, this does not indicate that buying ice cream causes sunburn. Instead, both may be influenced by a third factor, such as warm weather. Thus, correlation alone does not provide conclusive evidence of causative effects, which is why further investigation is always needed to explore the underlying dynamics of the observed correlation.