references.bib

@software{Li2023,
  title = {Friends {{Don}}'t {{Let Friends Make Bad Graphs}}},
  shorttitle = {Cxli233/{{FriendsDontLetFriends}}},
  author = {Li, Chenxin},
  date = {2023-01-16},
  doi = {10.5281/ZENODO.7542491},
  urldate = {2023-04-19},
  abstract = {Friends don't let friends make certain types of data visualization - What are they and why are they bad.},
  organization = {{Zenodo}},
  version = {v3}
}
@article{Weissgerber2015,
  title = {Beyond {{Bar}} and {{Line Graphs}}: {{Time}} for a {{New Data Presentation Paradigm}}},
  shorttitle = {Beyond {{Bar}} and {{Line Graphs}}},
  author = {Weissgerber, Tracey L. and Milic, Natasa M. and Winham, Stacey J. and Garovic, Vesna D.},
  date = {2015-04-22},
  journaltitle = {PLOS Biology},
  shortjournal = {PLOS Biology},
  volume = {13},
  number = {4},
  pages = {e1002128},
  publisher = {{Public Library of Science}},
  issn = {1545-7885},
  doi = {10.1371/journal.pbio.1002128},
  urldate = {2023-04-25},
  abstract = {Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.}
}

@online{Few2007,
  title = {Save the {{Pies}} for {{Dessert}}},
  author = {Few, Stephen},
  date = {2007-08},
  url = {www.perceptualedge.com/articles/08-21-07.pdf},
  urldate = {2023-04-27},
  organization = {{Visual Business Intelligence Newsletter}}
}

@online{Holtz,
  title = {The Issue with Pie Chart},
  author = {Holtz, Yan},
  url = {https://www.data-to-viz.com/caveat/pie.html},
  urldate = {2023-04-18},
  abstract = {A classification of chart types based on their input data format.},
}

@online{Nussbaumer2011,
  title = {Death to Pie Charts},
  author = {Nussbaumer, Cole},
  date = {2011-07-20},
  url = {https://www.storytellingwithdata.com/blog/2011/07/death-to-pie-charts},
  urldate = {2023-04-27},
  abstract = {I hate pie charts. I mean, really hate them.  In this post, I discuss why and show an illustrative makeover.},
  langid = {american},
  organization = {{storytelling with data}},
}

@inproceedings{Siirtola2019,
  title = {The {{Cost}} of {{Pie Charts}}},
  booktitle = {2019 23rd {{International Conference Information Visualisation}} ({{IV}})},
  author = {Siirtola, Harri},
  date = {2019-07},
  pages = {151--156},
  issn = {2375-0138},
  doi = {10.1109/IV.2019.00034},
  abstract = {Visualization of proportions is a very common need and there are many techniques for it. The pie chart is popular among practitioners and general audience, but many prominent experts advise against using it. This paper reports an experiment where the pie chart is compared to stacked bar charts with a baseline condition of table. The aim is to study if the performance differences justify the bad reputation of pie charts. In the experiment the participants were requested to list out the elements of a visualization in descending order of size. The task time and the answer were recorded. The results show that the pie chart is slower and less accurate than the stacked bar chart, especially when the difference between the elements is small, but the participants find it slightly more pleasant to use. The participants also perceive the stacked bar chart as the most effective visualization.},
  eventtitle = {2019 23rd {{International Conference Information Visualisation}} ({{IV}})},
  keywords = {Bars,Data visualization,Estimation,pie charts,stacked bar charts,Task analysis,TV,Visualization,visualization of proportions},
}

@dataset{Sheesley,
  title = {Light {{Bulb Lead Wire Weld Process Comparison}}},
  author = {Sheesley, John},
  url = {https://www.itl.nist.gov/div898/software/dataplot/data/SHEESLEY.DAT},
  urldate = {2023-05-03},
}

@online{StockholmInternationalPeaceResearchInstitute2022,
  title = {Top {{List TIV Tables}}},
  author = {{Stockholm International Peace Research Institute}},
  date = {2022},
  url = {https://armstrade.sipri.org/armstrade/page/toplist.php},
  urldate = {2023-05-03},
}