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When we see that two events are correlated (which we need some kind of statistics to do), we can tell a story (a theory, or an explanation) about how one event causes the other. If the explanation stands up to rational testing over time (where statistics are an important tool), then we have gained knowledge - one plausible explanation of what is "beyond appearances".

Therefore statistics are useful both before positing an explanation, and after to falsify it.



That theory or explanation requires the domain knowledge I am talking about.

Mere statistics about appearances is not enough.

To make it clear - statistics is obviously useful. It just cannot infer any proposition like x is y for all values of x.


I agree. I should have said that explicitly, before.




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