Z: Why vis?

Node: Visualizations make data errors obvious

Descriptor ObviousErrors
Argumentative standpoint Cognition
Description

A consistent mapping can reveal some errors in the data.

Last updated 3 years, 4 months ago (June 22, 2018) by Streeb, Dirk

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Publications (7)

F. J. Anscombe 1973 Graphs in Statistical Analysis 0 0 1 5 0
W. S. Cleveland and R. McGill 1985 Graphical Perception and Graphical Methods for Analyzing Scientific Data 0 0 1 5 0
H. Wainer 1990 Graphical Visions from William Playfair to John Tukey 0 0 1 8 0
J. T. Stasko 2014 Value-Driven Evaluation of Visualizations 0 0 1 13 0
M. Chen, L. Floridi and R. Borgo 2014 What is Visualization Really for? 0 0 1 8 0
P. C. Cheng 2016 What Constitutes an Effective Representation? 0 0 1 14 0
J. Gabry et al. 2018 Visualization in Bayesian Workflow 0 0 1 2 0
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Streeb, Dirk: J. T. Stasko [2014]: Value-Driven Evaluation of Visualizations doi:10.1145/2669557.2669579 - 19.03.18 10:16 (+) Positive One or more sentences sec. 3 Visualizations, and more specifically the visualization construction process, are a wonderful way to identify embedded problems in a data set such as missing, erroneous, or incomplete values.
Streeb, Dirk: W. S. Cleveland and R. McGill [1985]: Graphical Perception and Graphical Methods for Analyzing Scientific Data doi:10.1126/science.229.4716.828 - 18.03.18 11:39 (+) Positive One or more sentences p. 832 For example, using just the mean and standard deviation does not reveal outliers. Box plots give us more information about data distributions and allow us to appreciate the behavior of outliers.
Streeb, Dirk: H. Wainer [1990]: Graphical Visions from William Playfair to John Tukey doi:10.2307/2245821 - 12.03.18 08:16 (+) Positive One or more sentences p. 340 Such data characteristics as clerical errors in the Bills literally stuck out like sore thumbs.
Streeb, Dirk: J. Gabry et al. [2018]: Visualization in Bayesian Workflow - 08.03.18 13:44 (+) Positive One or more paragraphs p. 12 If we examine the data we find that this point is the only observation from Mongolia and corresponds to a measurement (x, y) = (log (satellite), log (PM 2.5 )) = (1.95, 4.32), which would look like an outlier if highlighted in the scatterplot in Figure 1b.
Streeb, Dirk: M. Chen, L. Floridi and R. Borgo [2014]: What is Visualization Really for? doi:10.1007/978-3-319-07121-3_5 - 26.01.18 08:53 (+) Positive
Streeb, Dirk: P. C. Cheng [2016]: What Constitutes an Effective Representation? doi:10.1007/978-3-319-42333-3_2 - 26.01.18 08:39 (+) Positive
Streeb, Dirk: F. J. Anscombe [1973]: Graphs in Statistical Analysis doi:10.2307/2682899 - 25.01.18 13:44 (+) Positive
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