We’ve all seen headlines before that say things like “More Sex Means More Money.” These headlines try to present the results of scientific studies in very simple and straightforward terms: if you do this, that will happen. However, what you’ll almost invariably find if you look past these claims is that they’re based on correlational data. This is a type of research in which scientists look to see how strongly two variables are statistically associated with one another. While correlational studies have the potential to be very informative and useful, the unfortunate reality is that they can’t tell us anything about whether one variable (like sex) truly causes another (like making more money).

Think of it this way: if you plotted sexual frequency and income on a graph with one variable on the X-axis and the other on the Y-axis, what you’d see is a pattern such that as one increases, the other tends to increase as well. While that might sound like pretty compelling evidence that one causes the other, it’s not. We can’t say with certainty why those variables appear to go together because in correlational research, there’s often a third variable—sometimes called a “lurking variable” or "confounding variable"—that accounts for the association.

For example, a third variable that could explain the link between sex and money is health. People who are in poor health tend to have less sex. Why? Poor health may not only reduce sexual desire, but also the pleasure experienced from sex. At the same time, people in poor health tend to make less money because their health status might affect their productivity at work. It could also affect their ability to maintain steady employment because they might be discriminated against.

All of this is simply to say that whenever you see a correlational study being hyped in the media—like one of these—be extra cautious when it comes to drawing conclusions, especially from the headlines. To learn more about how correlational research works and the problems that occur when we over-interpret it (including some examples relevant to sex and relationship research), check out the awesome video below from our friends over at ASAP Science.