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Open Access Publications from the University of California

Interpreting Data Tables: Can Variable Symmetry Scaffold Performance?


Data interpretation is crucial in modern society. One common data structure that people frequently encounter is 2 x 2 tables. Past work suggests that the nature of the variables affects how people interpret 2 x 2 tables. Specifically, people interpret tables with symmetric variables (present/present; e.g., treatment A vs. treatment B) more accurately than tables with asymmetric variables (present/absent; e.g., treatment vs. no treatment). This study tested whether interpreting tables with symmetric variables could scaffold later interpretation of tables with asymmetric variables. Undergraduates interpreted tables and rated the importance of each cell to their interpretations. Some participants interpreted tables with symmetric variables before tables with asymmetric variables; others interpreted only tables with asymmetric variables. Participants who first interpreted tables with symmetric variables later judged cells in the bottom row of asymmetric tables to be more important. Thus, experience with symmetric variables shifted participants’ views of tables with asymmetric variables.

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