What are the techniques to discriminate between coincidences, correlations, and real causation? Also, if you have a model where the response is highly correlated to (say) 5 non-causal variables and 2 direct causal variables, how do you assign a weight to the two causal variables? Can you provide examples of successful cause detection? In which contexts is it important to detect the true causes?…
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