Paper
1 May 1994 Visual inspection of data: does the eyeball fit the trend?
Gene S. Fisch, Anthony F. Porto
Author Affiliations +
Proceedings Volume 2179, Human Vision, Visual Processing, and Digital Display V; (1994) https://doi.org/10.1117/12.172677
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States
Abstract
Graphs are important tools for conveying quantitative information. However, studies have shown that visual inspection of data may not be very reliable. Therefore, it is essential to identify factors that affect visual inspection. We sought to determine how subjects' accuracy in visual inspection were affected when they constructed best-fitting lines to point-to-point functions generated by lag one auto-regressive equations. Subjects were tested then retested after completing a course on experimental methodology. When asked to identify treatment effects and/or trends, subjects mean correct responses were low (36%). On retest, their correct response rates showed little change. Mean correct responses to best-fitting lines was much higher (60%), and increased on retest (71%). The disparity between correct responses for identifying treatments and/or trends and constructing best-fitting lines was in part due to parameters in the auto-regression equation. Test-retest reliability was also better for best- fitting functions than for descriptive, multiple-choice responses. Subjects continue to demonstrate difficulty in separating trends from treatment effects.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gene S. Fisch and Anthony F. Porto "Visual inspection of data: does the eyeball fit the trend?", Proc. SPIE 2179, Human Vision, Visual Processing, and Digital Display V, (1 May 1994); https://doi.org/10.1117/12.172677
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Cited by 3 scholarly publications.
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KEYWORDS
Optical inspection

Reliability

Statistical analysis

Visualization

Analytical research

Data analysis

Visual analytics

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