what’s the difference between correlation and causation?
In: Other
Causation is a much more narrow, stronger, special case of correlation.
**Correlation** is simply whenever you notice thing B changing in some direction when thing A is changing in some direction. For example, overcast skies, grass being wet, and umbrella sales are all correlated with each other – in this case their odds increase when the other two increase.
Now, if I take a garden hose and start spraying my lawn with water, I wouldn’t expect skies to suddenly turning grey, nor is it a particularly great marketing campaign for my umbrella business. I also wouldn’t expect my special discount on umbrellas to do that, or to cause my lawn to become wet. On the other hand, if the clouds start gathering above, I **do** expect that I likely will be raking in the profits, but won’t need to turn the sprinklers on.
**Causation** is the reason why I expect that – in the model of the world that I currently find plausible, the way rain clouds work causes the other two things to happen, but none of the other two cause rain clouds to happen.
So, one way to think about causation is as a kind of an *asymmetric*, or *directed* correlation. Any causal relation will show correlation, but not all correlations are proof there’s causation.
Note that two things may cause each other – for example, in a ping-pong game, one player hitting the ball makes it more likely the other player will (because he couldn’t if the first guy butterfingered it), and the other player hitting back makes it more likely the first player will be able to hit it again – by the same logic.
Correlations are weak evidence, because they may pop up for all sorts of random reasons. The umbrella sales and the wet grass are correlated because they have a common cause, for example. Other times, it’s just plain stroke of luck that two unrelated things happened to play out at roughly the same time.
Latest Answers