Did you know that ice cream sales and shark attacks are highly correlated? The more ice cream people buy, the more times they are attacked by sharks. But does that mean you should stop eating ice cream in order to protect yourself from shark attacks? No, of course not. Ice cream sales don't cause shark attacks, and it would be a mistake to think so.
Although this case may be obvious, the line between correlation and causation is not always clear. Confusing one for the other is a common logical fallacy, especially among student debaters. In this article, we'll look at what this fallacy is, how to avoid it, and how to rebut it in the debating room.
When two things are correlated, it means there is a relationship between the two. Change in one variable is associated with a consistent change in the other, whether positive or negative.
Causation, on the other hand, means one variable causes the other. Change in one variable directly changes the other by means of cause and effect.
It can be easy to confuse these two ideas, since they both describe relationships between variables. However, they are quite different!
Let's go back to the example of ice cream sales and shark attacks. We see that these variables are correlated, and may be tempted to assume they have a causal relationship. But on second thought, it makes no sense that ice cream would cause shark attacks. This is correlation, not causation.
However, ice cream and shark attacks are related in another way. Both of them are caused by a third variable, that being the season of the year! In summer, more people are buying ice cream, and simultaneously, more people are swimming in the ocean, leading to a higher likelihood of shark attacks.
In addition to being linked by a third variable, other problems with confusing correlation and causation are that it may not be obvious which variable is causing which and, of course, the relationship may be a coincidence.
As you've probably gathered from the name, the correlation versus causation logical fallacy involves conflating correlation with causation.
In a debate, you might see your opponent arguing that violent video games lead to violence because rates of violent crime increased at the same time that computer games became more prevalent. Now, this may or not be true, but the evidence is far from definitive. Nothing this debater has said has demonstrated that video games are responsible for the increased rates of violent crime. One could just as easily point to a third factor that has caused the rise in both!
One good way to avoid this fallacy is to carefully consider the evidence or examples you're using to support your premise. If there isn't a causal relationship, don't invent one. If there is, make sure you clearly explain it.
In any debate, but especially parliamentary debate, it is important that you rely on logic and reasoning. Examples you cite should be at most illustrations of your argument. Try first explaining your argument without any examples, concentrating on the logic. If you're able to do this, you can add your examples back in to make your argument even stronger.
So you've stayed away from the correlation versus causation fallacy this debate. But you've caught your opponents using it. What do you do to combat their argument?
To rebut this fallacy, your job is to demonstrate that there could be other factors explaining the observed correlation or that the causal relationship is inverted. Bring up summer as the real reason for the relationship between ice cream sales and shark attacks.
Your rebuttal will be much stronger if you don't just point out that your opponents have made a fallacious argument, but explain why their claim of causation is incorrect. Showing how X does not cause Y will be much more persuasive to the judges than merely saying the opposing team has not shown the variables are causally related.
Whether in a school essay or a competitive debate, being aware of the correlation versus causation logical fallacy will strengthen your arguments and beliefs. It's one of several common fallacies that you may find wherever you go. Another you may have heard of before is the bandwagon fallacy.
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