Z: Why vis?

Publication: J. Gabry et al. [2018]: Visualization in Bayesian Workflow

Title Visualization in Bayesian Workflow
Authors
  1. Gabry, Jonah
  2. Simpson, Daniel
  3. Vehtari, Aki
  4. Betancourt, Michael
  5. Gelman, Andrew
Year 2018
DOI ---
ISBN ---
Open Access URL https://arxiv.org/abs/1709.01449
@misc{Gabry2018,
 title = {Visualization in {B}ayesian Workflow},
 author = {Gabry, Jonah and Simpson, Daniel and Vehtari, Aki and Betancourt, Michael and Gelman, Andrew},
 year = {2018},
 url = {https://arxiv.org/abs/1709.01449}
}

Last updated 11 months ago (Nov. 17, 2020) by Streeb, Dirk

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Visualizations make data errors obvious (+) 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: March 8, 2018
Visualizations reveal false assumptions (+) Positive Basically all of the publication Streeb, Dirk: March 8, 2018
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Streeb, Dirk March 8, 2018 June 6, 2018 2 0 0 Application focused
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