Abstract In the era of big data, an increasing amount of information is becoming available to business analysts and scientists. Statistical correlations between consumption patterns and individual conditions (e.g., health conditions) are frequently uncovered and reported in the media. However, many correlations are spurious, prompting the question of when consumers perceive them as reflecting causal relationships. Across eight preregistered studies, we demonstrate that a correlation (e.g., between drinking tea and bone health) is perceived as more likely to reflect a causal relationship (i.e., drinking tea makes bones healthier) when the plausible cause reportedly correlates with additional outcomes (e.g., heart conditions). The correlational scope effect is attenuated when the additional outcomes are perceived as weakly related to the focal outcome, mitigated under a cause-last framing (in which the plausible cause in a correlation is presented after the target outcome), and can influence product choices. We propose that category-based induction may contribute to the correlational scope effect: people project the perceived susceptibility to a cause from the additional outcomes onto the focal outcome. These findings have implications for our understanding of causal judgment and for consumers’ well-being.
Zhang et al. (Sat,) studied this question.