Column by Richard Sternberg

Correlation Doesn’t Imply Causation

I read a news report of a scientific article recently that was originally published in a reputable scientific journal that said something to the effect that multivitamins were good for the brain. I shared this with my daughters via text, one of whom is a real biomedical scientist. She retorted back almost immediately, “Dad, did you look at the original paper?” I hadn’t. She did. “Not only is the study flawed but there is not adequate evidence to suggest that there is a causative relationship. At best, and I am not sure, there is a mild correlation.”

Frequently I’m presenting in my columns the results of studies and the implication is that one thing led the other one to change. Unfortunately, that cannot be assumed. Unless the study is very well-designed, you could just as easily have the second finding affecting the first. In any event this is what it called a correlation. Correlation describes a relationship between variables: when one changes, the other also changes. A correlation is a “statistical indicator” of the relationship between variables. These variables change together but this change isn’t necessarily due to a direct or indirect causal link. A third variable, unseen, could cause both of the other variables to change. Causation means that changes in one variable directly bring about changes in the other; there is a cause-and-effect relationship between variables. The two variables are correlated with each other and there is also a causal link between them. Correlation does not imply causation, but causation requires a correlation.