It may be "dangerous", but basing causation just on correlation (or statistical data in general) is actually a pretty prominent idea: http://plato.stanford.edu/

It may be "dangerous", but basing causation just on correlation (or statistical data in general) is actually a pretty prominent idea: http://plato.stanford.edu/entries/causation-probabilistic/ http://plato.stanford.edu/entries/causation-probabilistic/. Chris Anderson obviously glosses over many tricky details, but Judea Pearl among others have written extensively on it. Ultimately, all these ideas can probably be traced back to David Hume (at least here in the West). Hank's argument that Chris is suggesting that we don't try to find spurious correlations is rather simplistic since a probabilistic theory of causation can account for "spurious" and "real" correlations quite well. Indeed, the only reason why we know that "spurious" correlations exist is because they eventually show up in the data (i.e. the economist finds out that the stock market does not predict sun spots). Thus, a statistical definition of causation (more or less one that only uses a notion of correlation), can actually be quite robust.