Timothy Heath from the University of South Florida (US) presented his work on when “good math” begets bad behavioral science in our <link marketing forschung research-seminar-series>Research Seminar Series.

In the course of his presentation, Timothy Heath reviewed four historically significant cases showing that “good math” (a preoccupation with, or blind reverence for, prevailing mathematical and statistical tools) has impaired scholarship for millennia while spawning two competing scholarly orientations that remain to this day: a causation orientation (understand the universe) that identifies underlying root causes that may yet lie beyond direct observation, and an engineering orientation (improve the universe) that predicts directly observed phenomena, typically with quantitative methods and models. Furthermore, he elaborated on cross-orientational conflicts with four examples (two culminating in suicide) before addressing six (time permitting) contemporary failings stimulated by “good math”: (1) considering unobserved heterogeneity an alternative explanation for between-subjects experiments, (2) interpreting ANOVA interactions in the residual means that test interactions, (3) using only correlational measures (Cronbach’s alpha, omega, factor analyses, etc.) for scale validation in experimental studies, and (4) presuming the veracity of prevailing value functions while holding that people (5) overweight smaller probabilities but (6) underweight larger probabilities.