Human processing of two‐dimensional graphics: Information‐volume concepts and effects in graph‐task fit anchoring frameworks

This report discusses the findings from three related experiments on the effects of information volume in graph‐task fit anchoring frameworks reported in the literature. Information volume is operationally defined as the size of a data matrix (SDM), that is, the total number of points in a graphical display. The anchoring frameworks specify that an extraction task has high or low x‐value anchoring depending on whether or not the x‐component is represented in the question (as a given or unknown value). A total within‐subject repeated measure experimental design was used to test the effects of SDM on speed and accuracy of data extraction. These experiments also integrated different frameworks to relate the information‐volume effects. Results indicated that increased SDM adversely affected only data extraction time, not accuracy. A significant graph format by information volume interaction was observed; and training did reduce perceived information complexity, especially for high data volume displays. Also, effects of information volume on graph types differed: For vertical bars, a steeply rising monotonic performance‐information volume trend was observed for all tasks. Symbols produced flat nonmonotonic trends for high x‐value anchoring tasks and a gently rising monotonie trend for low x‐value anchoring tasks. In contrast, line graphs produced a gently rising monotonie trend for high x‐value anchoring tasks and a nonmonotonic trend for low x‐value anchoring tasks. Such evidence suggests that information volume effects on human processing of two‐dimensional graphical displays are influenced considerably by the character of the graphic format used for representing quantitative data and by the “fit” in anchoring characteristics between tasks and graphical formats.