I don't understand why everyone calls the correlation between the number of storks and childbirths per country as "spurious". That's incorrect. There is absolut

I don't understand why everyone calls the correlation between the number of storks and childbirths per country as "spurious". That's incorrect. There is absolutely a correlation, but it is the statement that the fabricated cause of that correlation as presented (i.e. storms deliver babies) is true that is spurious. The truth underpinning the correlation (i.e. increased country size tends to yield increased populations of flora/fauna of all varieties) requires additional data to reveal - especially, in this case, if your a person who has never heard of a "stork" or what one is. The p-value tells researchers that there's something interesting going on between data sets and further exploration is likely warranted to reveal the true underlying relationship. It's not a proof of a fabricated conclusion. "The golden way to test a causal relation is an appropriately designed experiment, where only the suspected "cause" is varied and the "effect" is observed." 1. https://www.researchgate.net/post/If_correlation_doesnt_imply_causation_then_if_I_find_a_statistically_significant_correlation_how_can_I_prove_the_causality https://www.researchgate.net/post/If_correlation_doesnt_impl...