Everyone who takes basic statistics has it drilled into them that “correlation is not causation.” (When I took psych. 1, the professor said he hoped that, if he were to come to us on our death-beds and prompt us with “Correlation is,” we would all respond “not causation.”) This is a problem, because one can infer correlation from data, and would like to be able to make inferences about causation. There are typically two ways out of this. One is to perform an experiment, preferably a randomized double-blind experiment, to eliminate accidental sources of correlation, common causes, etc. That’s nice when you can do it, but impossible with supernovae, and not even easy with people. The other out is to look for correlations, say that of course they don’t equal causations, and then act as if they did anyway.
That said… treating correlations as evidence of causation isn’t unreasonable, as long as I remember that the world is full of evidence of falsehoods as well as truths, and calibrate accordingly.
-- Cosma Shalizi on Graphical Models
Obligatory xkcd reference
That said… treating correlations as evidence of causation isn’t unreasonable, as long as I remember that the world is full of evidence of falsehoods as well as truths, and calibrate accordingly.
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Far too true. :)
Far too true. :)