<i>Would you like to elaborate about &quot;somewhat wrong&quot;, with quotations from Principles of Mathematics, for example?</i><p>It&#x27;s &quot;somewhat wrong&quot; because in some cases it is possible to derive causation using statistical methods.<p>Have you read the linked book? It should answer your questions. If not I&#x27;ll point you to Michael Nielsen&#x27;s post[1], where he <i>explain[s] how the causal calculus can sometimes (but not always!) be used to infer causation from a set of data, even when a randomized controlled experiment is not possible. Also in the post, I’ll describe some of the limits of the causal calculus</i><p>It&#x27;s a pretty long post, but the gist of it is that in some circumstances it&#x27;s possible to build a world model of an imaginary controlled, randomized experiment and then see if non-controlled, real world data matches those expectations.<p>What that gives you is a distribution of the probabilities of causality.<p>[1] <a href="http:&#x2F;&#x2F;www.michaelnielsen.org&#x2F;ddi&#x2F;if-correlation-doesnt-imply-causation-then-what-does&#x2F;" rel="nofollow">http:&#x2F;&#x2F;www.michaelnielsen.org&#x2F;ddi&#x2F;if-correlation-doesnt-impl...</a>