Proceedings of the Annual Meeting of the Cognitive Science Society

When estimating the strength of the relation between a cause(X) and effect (Y), there are two main statistical approachesthat can be used. The first is using a simple correlation. Thesecond approach, appropriate for situations in which thevariables are observed unfolding over time, is to take acorrelation of the change scores – whether the variablesreliably change in the same or opposite direction. The mainquestion of this manuscript is whether lay people use changescores for assessing causal strength in time series contexts.We found that subjects’ causal strength judgments were betterpredicted by change scores than the simple correlation, andthat use of change scores was facilitated by naturalisticstimuli. Further, people use a heuristic of simplifying themagnitudes of change scores into a binary code (increase vs.decrease). These findings help explain how people uncovertrue causal relations in complex time series contexts.