Predicting values and trends from tables and graphs

Marcia Kuskin Shamo, Joachim Meyer, Daniel Gopher

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

The issue of optimal display design was re-examined under the hypothesis that the nature of the data set would influence the efficacy of displays. An experiment assessed the effect of data structures on the relative efficacy of line graphs and tables. Participants saw a sequence of graphic or tabular displays which presented data from functions. The displays showed either values taken from the simple form of a single sinusoid function (structured data conditions), or from the complex and seemingly unstructured form of five summed sinusoid functions (unstructured data conditions). After seeing four consecutive displays participants were asked to predict the behavior of the data set in the next display which they had not yet seen. They were required to predict either the behavior of specific points, or the direction of trends. While the performance of the point comparison task was not influenced by display format, graphs were found to have an advantage for the prediction of future trends. Graphs also led more frequently to the identification of structure than did tables, both for structured and unstructured conditions.

Original languageEnglish
Pages (from-to)1151-1154
Number of pages4
JournalProceedings of the Human Factors and Ergonomics Society
Volume2
StatePublished - 1 Jan 1996
Externally publishedYes
EventProceedings of the 1996 40th Annual Meeting of the Human Factors and Ergonomics Society. Part 1 (of 2) - Philadelphia, PA, USA
Duration: 2 Sep 19966 Sep 1996

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