Correlation is Not Causation
Correlational research is useful because it allows us to discover the strength and direction of relationships that exist between two variables. However, correlation is limited because establishing the existence of a relationship tells us little about cause and effect. While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the change in our variable. In the ice cream/crime rate example mentioned earlier, temperature is a confounding variable that could account for the relationship between ice cream and crime rates.
Even when we cannot point to clear confounding variables, we should not assume that a correlation between two variables implies that one variable causes changes in another. This can be frustrating when a cause-and-effect relationship seems clear and intuitive. For example, while it seems reasonable to assume that smoking causes cancer, if we were limited to correlational research, we would be overstepping our bounds by making this assumption.
Unfortunately, people mistakenly make claims of causation as a function of correlations all the time. Such claims are especially common in advertisements and news stories. For example, one study found that people who eat cereal on a regular basis achieve healthier weights than those who rarely eat cereal (Frantzen, Treviño, Echon, Garcia-Dominic, & DiMarco, 2013; Barton et al., 2005). Guess how the cereal companies report this finding? Does eating cereal really cause an individual to maintain a healthy weight, or are there other possible explanations? While correlational research is invaluable in identifying relationships among variables, a major limitation is the inability to establish causality.
Illusory Correlations
The temptation to make false cause-and-effect statements based on correlational research is not the only way we tend to misinterpret data. We also tend to make the mistake of illusory correlations, especially with unscientific observations. Illusory correlations, or false correlations, occur when people believe that relationships exist between two things when no such relationship exists. One well-known illusory correlation is the supposed effect that the moon’s phases have on human behavior. Many people passionately assert that human behavior is affected by the phase of the moon, and specifically, that people act strangely when the moon is full.
There is no denying that the moon exerts a powerful influence on our planet. The ebb and flow of the ocean’s tides are tightly tied to the gravitational forces of the moon. Many people believe, therefore, that it is logical that we are affected by the moon as well. After all, our bodies are largely made up of water. A meta-analysis of nearly 40 studies consistently demonstrated, however, that the relationship between the moon and our behavior does not exist (Rotton & Kelly, 1985). While we may pay more attention to odd behavior during the full phase of the moon, the rates of odd behavior remain constant throughout the lunar cycle. More recent studies, however, have been able to draw some parallels between the moon phases and sleep quality and quantity, but the implications of this are yet to be determined.
So why are we so apt to believe in illusory correlations? Often we read or hear about them and simply accept the information as valid. Or, we have a hunch about how something works and then look for evidence to support that hunch, ignoring evidence that would tell us our hunch is false; this is known as confirmation bias.
Other times, we find illusory correlations based on the information that comes most easily to mind, even if that information is severely limited. For example, research suggests that illusory correlations about certain groups of people lead to the formation of prejudicial attitudes that can ultimately lead to discriminatory behavior (Fiedler, 2004).