Judgments of Proportion with Graphs: Object-Based Advantages

Abstract

This study investigated whether a stacked bar's vertical arrangement or single-object properties underlie its accuracy for proportion judgments. We hypothesized that observers would be less accurate when stacked bars were separated than when they formed a single object, according to the object-based theory of attention (Duncan, 1984). Thirty participants judged proportions with three different graph types: bars, stacked bars, and staggered stacked bars. Stacked bars produced smaller error than staggered stacked bars, while bars produced the greatest error. The results show an object-based advantage for stacked bars, but a vertical arrangement advantage for staggered stacked bars over bars was also evident.

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References

Baylis

G. C.

Driver

(1993). Visual attention and objects: Evidence for hierarchical coding of location. Journal of Experimental Psychology: Human Perception and Performance, 19, 451–470.

Cleveland

W. S.

McGill

(1984). Graphical perception: Theory, experimentation, and application to the development of graphical methods. Journal of the American Statistical Association, 79, 531–554.

Duncan

(1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501–517.

Follette

(2000). Comparing the effectiveness of bar and slacked bar graphs for judgments of proportion. Unpublished Master's Thesis. University of Idaho, Department of Psychology.

Follette

Hollands

J. G.

(1998, October). Bars vs stacked bars: Effectiveness is task dependent. Poster presented at the 42nd Annual Meeting of the Human Factors and Ergonomics Society, Chicago, IL.

Hollands

J. G.

Spence

(1992). Judgments of change and proportion in graphical perception. Human Factors, 34, 313–334.

Hollands

J. G.

Spence

(2001). The discrimination of graphical elements. Applied Cognitive Psychology, 15, 413–431.

Loftus

G. R.

Masson

M. E. J.

(1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin and Review, 1, 476–490.

Rayson

J. K.

(1999). Aggregate towers: Scale sensitive visualization and decluttering of geospatial data. Proceedings IEEE Symposium on Information Visualization (pp. 92–99. San Francisco: IEEE Computer Society.

10.

Vecera

S. P.

Farah

M. J.

(1994). Does visual attention select objects or locations? Journal of Experimental Psychology: General, 123, 146–160.