Cleveland mcgill 1984

View on AAAS. Save to Library Save. Create Alert Alert. Share This Paper. Background Citations. Methods Citations. Results Citations. Topics from this paper. Computer graphics Chart. Binary number Smoothing statistical technique. Paper Mentions. Blog Post. Simply Statistics. News Article. Signifikanztest: Statistik: Der p-Wert ist das kleinste Problem!

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More Filters. Models of Graphical Perception. Analysis of the perception of graphical encodings for information visualization. Information Visualization concerns the use of interactive computer graphics to enable people to obtain insight in large amounts of abstract data.

To this end, data objects and their attributes have … Expand. Highly Influenced. View 7 excerpts, cites methods, background and results. Process and representation in graphical displays. Density in scatterplots and the estimation of correlation. An experimental program investigating color-enhanced and graphical information presentation: an integration of the findings. View 1 excerpt, cites results.

Publisher Summary The emphasis on structural variables alone is insufficient to account for many aspects of graphical communication, even those associated with variations in the efficacy of different … Expand. View 1 excerpt, cites background. An Experiment in Graphical Perception. Representation and recognition of the spatial organization of three-dimensional shapes. Cleveland also furthered his discussion of how people perceive charts, and which visual representations are best for which data.

He recommends that data points be put as close together as possible, because people more accurately compare elements that are closer together. The following shows two visualizations of the country location of Udemy Users.

The stacked bar chart also receives Cleveland disdain, he demonstrates that people understand aligned bar charts substantially better than stacked ones. Noted statisticians and data visualization experts Stephen Few , Nathan Yau and Hadley Wickham have all discussed being influenced by the ideas of Cleveland. Each of them has written books that espouse ideas Cleveland developed. Many data visualization experts see Cleveland as creating the basic rules for chart makers to follow.

But, as the saying goes, rules were made to be broken, or at least bent. As data visualization has grown more creative and interactive , it remains grounded by the scientific foundation provided by William Cleveland.

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