 Both Bandyopadhyay et al. and Fitelson claim that because the formulation of Simpson’s paradox does not itself appeal to causal considerations, it is a preferable to find a non-causal explanation for the paradox. Ultimately, it is an empirical question whether the paradox can be accounted for exclusively by errors in probabilistic reasoning, or, as Pearl suggests, due to a conflation of causal and probabilistic reasoning. One conceptual barrier to disentangling these hypotheses is that there are systematic relationships between causal and probabilistic claims For example, when the third variable \(\r{M}\) is uncorrelated with treatment \(T\) (i.e., \(p(\r{T}\mid \r{M}) = p(\r{T})\)), there can be no reversals (see also the theorems in  Section 2.2).  Does it follow that Simpson’s Paradox has a purely probabilistic explanation? Not necessarily. An alternative hypothesis is that the epistemic agent does not have knowledge of the relevant conditional probabilities, but does know that \(M\) is not a cause of \(T\) \((p(\r{T}\mid \do(\r{M})) = p(\r{T})\)), preempting the occurrence of association reversals. The question of whether the source of the paradox is causal cannot be resolved purely by appeal to the mathematical conditions under which the it arises. Rather, it depends on substantive psychological hypotheses about the role of causal and probabilistic assumptions in human  reasoning.[10]