Graphical perception
This sandbox is in the article namespace. Either move this page into your userspace, or remove the {{User sandbox}} template. Graphical perception is the visual decoding of the quantitative and qualitative information encoded on graphs.[1] The importance of human graphical perception, what we discern easily versus what our brains have more difficulty decoding, is fundamental to good statistical graphics design, where clarity, transparency, accuracy and precision in data display and interpretation are essential for understanding science.[2][3][4][5][6]
Cleveland's and McGill's experiments[1] to elucidate the graphical elements humans perceive most accurately is a fundamental component of good statistical graphics design principles. Humans perceive relative position on a common scale most accurately; a graph type that utilizes this graphics element is the dot plot. Angles are perceived with less accuracy; an example is the pie chart.
Graphic design that takes into consideration visual pre-attentive processing such as pattern perception is why a picture can be worth a thousand words. Not all graphs are designed to consider pre-attentive processing. A commonly used graphic design feature, similar to a lookup table, requires the brain to work harder and take longer to see the data comparison.[3]
References
- ^ a b Cleveland, William; McGill, Robert (1984). "Graphical Perception and Graphical Methods for Analyzing Scientific Data". Journal of the American Statistical Association. 79: 531–544.
- ^ Cleveland, William (1993). Visualizing Data. Summit, New Jersey: Hobart Press. ISBN 0-9634884-0-6.
- ^ a b Cleveland, William (1994). The elements of graphing data. Summit, New Jersey: Hobart Press. ISBN 0-9634884-1-4.
- ^ Tufte, Edward (2001). The Visual Display of Quantitative Information. Cheshire, Connecticut: Graphics Press. ISBN 1930824130.
- ^ Duke, Susan; Bancken, Fabrice; Crowe, Brenda; Soup, Mat; Boots's, Taxiarchis; Forshee, Richard (2015). "Seeing is believing: good graphic design principles for medical research". Statistics in Medicine. 34: 3040–3059.
- ^ Angra, Aakanksha; Gardner, Stephanie (2017). "Reflecting on Graphs: Attributes of Graph Choice and Construction Practices in Biology". CBE—Life Sciences Education. 16: 1–15.
External links
- [1]Here is a brief description and picture of Cleveland and McGill's[1] nine graphical elements
- [2] "How William Cleveland Turned Data Visualization Into a Science" (2016) from Priceonomics.com
- [3] John Rauser's 2016 presentation, "How Humans See Data" at Velocity Amsterdam. Describes how good visualizations optimize for the human visual system
- [4]Michael Friendly's Gallery of Data Visualization: The Best and Worst of Statistical Graphics
Graphical Perception
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