The relationship between correlation and causation is best summarized as:

The relationship between correlation and causation is that correlation can suggest a potential causal relationship, but it does not confirm it. This means that when two variables are correlated, there might be a reason to investigate further to identify if one variable influences the other. However, correlation alone does not provide definitive proof of causation. Other factors, such as the presence of confounding variables or reverse causality, can complicate the relationship.

For example, just because there is a strong correlation between ice cream sales and the incidence of sunburns does not mean that buying ice cream causes sunburns; instead, both factors are likely influenced by the presence of hot weather. Therefore, determining whether a correlation reflects a causal relationship requires further analysis and cannot be established solely based on the correlation coefficient.

In contrast, the other choices misinterpret the nature of the relationship. Negative correlation does not indicate causation, causation can exist without correlation in some contexts (for example, if a third variable influences both), and a correlation higher than 0.9 still does not imply causation without further evidence.