This paper is from Session 7A: Statistics and the media
Full topic list
which comes under Topic 7: Statistics education and the wider society

(Monday 12th, 11:00-12:30)

Association-causation problems in news stories


  • Milo Schield (Keck Statistical Literacy Project, United States)


Statistical educators strongly emphasize the importance of distinguishing association and causation. Yet this semantic distinction is often obscured due to an inappropriate choice of words. This paper investigates related problems–inaccuracies, omissions and ambiguities–in numberbased news stories. It investigates association-related problems involving large numbers, confusion of the inverse, missing context, times-less and times-more comparisons, incomplete comparisons, slope comparisons and confusing “frequently” with “likely.” It investigates causation-related problems involving causation words and action verbs. These problems may create reader confusion and misunderstanding. Data is needed on how readers understand the presentation of association and causation in the media. Statistical educators, journalism faculty and quantitative journalists should join together in analyzing these problems in number-based news stories.