'correlation does not equal causation.'

When it comes to the scientific method, the first thing that comes to mind is the phrase, 'correlation does not equal causation.' This is a basic tenants of science that is often used by skeptics and anti-theists to dismiss arguments made by people who are not scientists.

However, this phrase is often misunderstood or misused. Just because two things are correlated does not mean that one caused the other. However, most likely it does unless you are trying to blame two unrelated situations or examples.

For example, let's say that you were to measure the height of everyone in your class. You would then notice that there is a correlation between height and weight. Does this mean that being taller causes you to weigh more?

No, of course not. We know that there are other factors at play, such as genetics and diet. However, in this case, the correlation is still useful as it can help us to understand the relationship between height and weight.

There are, of course, cases where the correlation does equal causation. For example, if you were to measure the amount of time spent studying and the grades achieved, you would find a strong correlation. In this case, we can say with confidence that causation does equal correlation.

A lot of people these days like to say 'correlation does not equal causation' as if it's some kind of magical incantation that makes all arguments against their position disappear. It's a favorite of skeptics and anti-theists, and they love to trot it out whenever someone tries to point out that their worldview doesn't make sense.

The problem is that they almost always use it out of context, or they simply don't understand what it means. Let's take a look at what the phrase actually means, and how it applies (or doesn't apply) to various situations.

First of all, 'correlation' simply means that two things are related. It doesn't say anything about how they're related, or whether one causes the other. For example, there is a strong correlation between smoking and lung cancer. But that doesn't mean that smoking *causes* lung cancer. It could be that people who are more likely to get lung cancer are also more likely to smoke, or there could be some other factor that causes both smoking and lung cancer.

'Causation' means that one thing causes another. So if smoking *causes* lung cancer, then we would expect to see a strong correlation between the two. But again, correlation does not equal causation. Just because two things are related does not mean that one causes the other.

So when someone says 'correlation does not equal causation,' they're simply pointing out that you can't assume that two things are related just because they're correlated. You need to look at other evidence to determine whether or not there is a causal relationship.

Now, does this mean that correlation can never equal causation? No, it doesn't. There are situations where the evidence strongly suggests that correlation does indeed equal causation. For example, there is a strong correlation between drinking alcohol and getting drunk. In this case, it is pretty clear that the alcohol *causes* the drunkenness.

The same is true of many other things. There is a strong correlation between eating junk food and being overweight, between not exercising and being out of shape, and so on. In these cases, the correlation is almost certainly due to causation.

So when can you say for sure that correlation equals causation? Generally speaking, you need to have a lot of evidence to be sure. A single correlation, by itself, is not enough. But if you have multiple correlations, from different sources, all pointing in the same direction, then you can be pretty confident that causation is involved.

So the next time someone trots out the old 'correlation does not equal causation' line, don't be fooled. It's a meaningless phrase unless you understand the context in which it's being used

So, the next time someone tries to dismiss your argument by saying, 'correlation does not equal causation,' ask them to explain the context in which this phrase is being used. Chances are, they don't really understand what they're saying.