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Causal Inference and Statistical Fallacies

2001

Fallacies are defined as plausible-seeming arguments that give the wrong conclusion. The article concentrates on those with some connection with causality. The classical definition of causality involving a necessary and sufficient condition for an effect is rejected and three possible definitions discussed. The first is that of a statistical association that cannot be explained away as the effect of admissible alternative features. To make this more precise, Markov graphical representations are introduced and the important distinction between pairs of variables on an equal footing and those in a potential explanatory-response relation described. The roles of unobserved confounders and of ra…

Counterfactual thinkingMarkov chainArgumentCausal inferenceReading (process)media_common.quotation_subjectRelation (history of concept)Mathematical economicsCausalitySocial psychologyMisuse of statisticsMathematicsmedia_common
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