Quote:
Originally Posted by johnt
You are both correct: correlation does not imply causation.
But, it seems to me, rather unsatisfactory to leave it there.
In life we have to continually make decisions: do we do this exercise or that, do we take a particular supplement or not, do we start to take levodopa now or not. Often there is little or no data to help us make our decision. Often we are forced by circumstances to make a decision now.
In these situations we are forced to rely on experience (often barely relevant) and whatever data we may find (often poor quality).
Put another way, on the evidence presented in the article, and ignoring cost, is there a better course of action?
John
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John, the problem is really one of the media. They love to highlight and promote research findings when they find correlated items without properly disclosing that there may in-fact be no direct or indirect causation. As a matter of fact, many of the studies clearly point out the inability to determine if there is any causation and the media just overlooks that point.
Unfortunately, you can't ignore cost and many times there may be better course of action, or inaction. Too many people act on correlated studies only to find out later that there is no actual direct casual relationship.
Making a decision on correlated variables that appear to be logical doesn't always turn out to be correct. Unfortunately, our intuition can lead us astray when it comes to distinguishing between causality and correlation. For example, there have been many studies showing that not eating breakfast is strongly correlated with poor performance in elementary school. It would be easy to conclude that eating breakfast causes students to be smarter. However, when actual controlled studies were done, eating breakfast did not cause higher grades. It turns out that not eating breakfast was also correlated with two other variables, absences and tardiness, which were the actual causes of the lower performance.
In general, we should all be wary of our own bias; we like explanations. The media often concludes a causal relationship among correlated observances when causality was not even considered by the study itself. Without clear reasons to accept causality, we should only accept correlation. Two events occurring in close proximity does not imply that one caused the other, even if it seems to makes perfect sense.