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Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
Published on: June 21, 2019
Bars and lines: a study of graphic communication
Memory & Cognition
|December 10, 1999
Summary
People naturally associate bar graphs with discrete data comparisons and line graphs with trends. This intuitive graph interpretation stems from cognitive principles, not learned rules, influencing how we process visual information.
Area of Science:
- Cognitive Science
- Information Visualization
- Human-Computer Interaction
Background:
- Graph interpretation often relies on assumed correspondences between visual elements and data types.
- Previous research has not fully elucidated the underlying cognitive principles driving these associations.
Purpose of the Study:
- To investigate whether graph interpretation is based on cognitive naturalness and information processing principles.
- To determine if specific graph types (bars, lines) are inherently associated with particular data representations (discrete comparisons, trends).
Main Methods:
- Three experiments were conducted, focusing on graph comprehension and production.
- Participants' associations between graph types and data representation were analyzed.
Main Results:
- Findings supported the hypothesis that bars are associated with discrete comparisons due to their discrete nature.
- Lines were readily associated with trends, reflecting their ability to represent slope and continuity.
- These correspondences were observed regardless of explicit knowledge of graphing rules.
Conclusions:
- Graph interpretation appears to be driven by cognitive naturalness and perceptual properties, aligning visual elements with data characteristics.
- The communicative situation and inherent visual features of graphs significantly influence interpretation.
- These findings suggest a foundation for more intuitive and effective data visualization design.
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