Z: Why vis?

Node: Visualizations reveal false assumptions

Descriptor FalseAssumptions
Argumentative standpoint Cognition
Description

A visualization can make false assumptions (accidentally) made for analytical analysis obvious. For example, superimposing a histogram with an expected density of an assumed distribution may show differences clearly, and thereby hint at questioning the distribution assumption.

Last updated 3 years ago (June 22, 2018) by Streeb, Dirk

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Publications (5)

F. J. Anscombe 1973 Graphs in Statistical Analysis 0 0 1 5 0
J. Fekete et al. 2008 The Value of Information Visualization 0 0 1 12 0
A. Gelman and A. Unwin 2013 Infovis and Statistical Graphics: Different Goals, Different Looks 0 0 1 21 2
D. A. Szafir et al. 2016 Four Types of Ensemble Coding in Data Visualizations 0 0 1 10 0
J. Gabry et al. 2018 Visualization in Bayesian Workflow 0 0 1 2 0
Authors Year Title Codings Coded entities
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Codings (5)

Streeb, Dirk: J. Gabry et al. [2018]: Visualization in Bayesian Workflow - 08.03.18 13:44 (+) Positive Basically all of the publication
Streeb, Dirk: A. Gelman and A. Unwin [2013]: Infovis and Statistical Graphics: Different Goals, Different Looks doi:10.1080/10618600.2012.761137 - 27.02.18 16:15 (+) Positive One or more sentences p. 7 Giving an overview—a qualitative sense of what is in a dataset, checking assumptions, confirming known results, and looking for distinct patterns.
Streeb, Dirk: J. Fekete et al. [2008]: The Value of Information Visualization doi:10.1007/978-3-540-70956-5_1 - 26.02.18 12:44 (+) Positive One or more sentences p. 13 It remains remarkably effective at filtering-out noise from useful data…
Streeb, Dirk: F. J. Anscombe [1973]: Graphs in Statistical Analysis doi:10.2307/2682899 - 25.01.18 13:44 (+) Positive
Streeb, Dirk: D. A. Szafir et al. [2016]: Four Types of Ensemble Coding in Data Visualizations doi:10.1167/16.5.11 - 24.01.18 12:57 (+) Positive
Coding Affirmation Extent Reference Quote

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