Summaries

Part-Whole.bib

@@ -94,6 +94,25 @@ @article{clevelandGraphicalPerceptionTheory1984
   file = {/Users/cbbcbail/Zotero/storage/6WYNCPNR/Cleveland and McGill - 1984 - Graphical Perception Theory, Experimentation, and.pdf}
 }
 
+@article{clevelandGraphicalPerceptionVisual1987,
+  title = {Graphical {{Perception}}: {{The Visual Decoding}} of {{Quantitative Information}} on {{Graphical Displays}} of {{Data}}},
+  shorttitle = {Graphical {{Perception}}},
+  author = {Cleveland, William S. and McGill, Robert},
+  year = {1987},
+  journal = {Journal of the Royal Statistical Society. Series A (General)},
+  volume = {150},
+  number = {3},
+  eprint = {2981473},
+  eprinttype = {jstor},
+  pages = {192--229},
+  publisher = {[Royal Statistical Society, Wiley]},
+  issn = {0035-9238},
+  doi = {10.2307/2981473},
+  urldate = {2024-03-18},
+  abstract = {Studies in graphical perception, both theoretical and experimental, provide a scientific foundation for the construction area of statistical graphics. From these studies a paradigm that has important applications for practice has begun to emerge. The paradigm is based on elementary codes: Basic geometric and textural aspects of a graph that encode the quantitative information. The methodology that can be invoked to study graphical perception is illustrated by an investigation of the shape parameter of a two-variable graph, a topic that has had much discussion, but little scientific study, for at least 70 years.},
+  file = {/Users/cbbcbail/Zotero/storage/364Z8U77/Cleveland and McGill - 1987 - Graphical Perception The Visual Decoding of Quant.pdf}
+}
+
 @article{converseRoleProminentNumbers2018,
   title = {The Role of ``{{Prominent Numbers}}'' in Open Numerical Judgment: {{Strained}} Decision Makers Choose from a Limited Set of Accessible Numbers},
   shorttitle = {The Role of ``{{Prominent Numbers}}'' in Open Numerical Judgment},
@@ -128,6 +147,39 @@ @article{croxtonBarChartsCircle1927
   file = {/Users/cbbcbail/Zotero/storage/RE9JZ59I/Croxton and Stryker - 1927 - Bar Charts Versus Circle Diagrams.pdf}
 }
 
+@article{croxtonGraphicComparisonsBars1932a,
+  title = {Graphic {{Comparisons}} by {{Bars}}, {{Squares}}, {{Circles}}, and {{Cubes}}},
+  author = {Croxton, Frederick E.},
+  year = {1932},
+  journal = {Journal of the American Statistical Association},
+  volume = {27},
+  number = {177},
+  eprint = {2277880},
+  eprinttype = {jstor},
+  pages = {54--60},
+  publisher = {[American Statistical Association, Taylor \& Francis, Ltd.]},
+  issn = {0162-1459},
+  doi = {10.2307/2277880},
+  urldate = {2024-03-18},
+  file = {/Users/cbbcbail/Zotero/storage/QSQ8VGE2/Croxton - 1932 - Graphic Comparisons by Bars, Squares, Circles, and.pdf}
+}
+
+@article{culbertsonStudyGraphComprehension1959,
+  title = {A {{Study}} of {{Graph Comprehension Difficulties}}},
+  author = {Culbertson, Hugh M. and Powers, Richard D.},
+  year = {1959},
+  journal = {Audio Visual Communication Review},
+  volume = {7},
+  number = {2},
+  eprint = {30216875},
+  eprinttype = {jstor},
+  pages = {97--110},
+  publisher = {Springer},
+  issn = {0885-727X},
+  urldate = {2024-03-18},
+  file = {/Users/cbbcbail/Zotero/storage/XM458YMX/Culbertson and Powers - 1959 - A Study of Graph Comprehension Difficulties.pdf}
+}
+
 @article{cummingNewStatisticsWhy2014,
   title = {The {{New Statistics}}: {{Why}} and {{How}}},
   shorttitle = {The {{New Statistics}}},
@@ -337,6 +389,24 @@ @book{kosaraJudgmentErrorPie2016
   file = {/Users/cbbcbail/Zotero/storage/Q9N3GB4D/Kosara and Skau - 2016 - Judgment Error in Pie Chart Variations.pdf}
 }
 
+@inproceedings{kosaraMechanicalTurksDream2010,
+  title = {Do {{Mechanical Turks}} Dream of Square Pie Charts?},
+  booktitle = {Proceedings of the 3rd {{BELIV}}'10 {{Workshop}}: {{BEyond}} Time and Errors: Novel {{evaLuation}} Methods for {{Information Visualization}}},
+  author = {Kosara, Robert and Ziemkiewicz, Caroline},
+  year = {2010},
+  month = apr,
+  series = {{{BELIV}} '10},
+  pages = {63--70},
+  publisher = {Association for Computing Machinery},
+  address = {New York, NY, USA},
+  doi = {10.1145/2110192.2110202},
+  urldate = {2024-03-18},
+  abstract = {Online studies are an attractive alternative to the laborintensive lab study, and promise the possibility of reaching a larger variety and number of people than at a typical university. There are also a number of draw-backs, however, that have made these studies largely impractical so far. Amazon's Mechanical Turk is a web service that facilitates the assignment of small, web-based tasks to a large pool of anonymous workers. We used it to conduct several perception and cognition studies, one of which was identical to a previous study performed in our lab. We report on our experiences and present ways to avoid common problems by taking them into account in the study design, and taking advantage of Mechanical Turk's features.},
+  isbn = {978-1-4503-0007-0},
+  keywords = {empirical studies,Mechanical Turk},
+  file = {/Users/cbbcbail/Zotero/storage/A2B8W6A3/Kosara and Ziemkiewicz - 2010 - Do Mechanical Turks dream of square pie charts.pdf}
+}
+
 @article{lewandowskyPerceptionStatisticalGraphs1989,
   title = {The {{Perception}} of {{Statistical Graphs}}},
   author = {Lewandowsky, Stephan and Spence, Ian},
@@ -372,6 +442,22 @@ @article{melodycarswellGraphingDepthPerspectives1991
   abstract = {Embellishing simple graphs by adding perspective, 'the 3D look, has become increasingly commonplace with the ready availability of graphics software. However, the effect of adding such decorative depth on the comprehension and recall of the graph's message has received little attention. The present study evaluated performance on such common graphical formats as line graphs, bar charts and pie charts constructed with and without the 3D look. When subjects were asked to make relative magnitude estimations, only the 3D line graphs resulted in reliable performance decrements. Likewise, information presented in 3D line graphs was remembered less accurately than information presented in 2D line graphs. For the estimation of global trends, both 3D line graphs and bar charts were used more quickly than 2D formats, but this speed was obtained at the expense of accuracy. For a trend classification task involving more focused processing, 3D line graphs and bar charts were associated with an overall performance decrement when compared with their 2D counterparts. Finally, the use of 3D designs, in addition to modifying performance, may influence the attitudes formed by subjects toward the information presented in the graphs.}
 }
 
+@article{petersonHowAccuratelyAre1954,
+  title = {How {{Accurately Are Different Kinds}} of {{Graphs Read}}?},
+  author = {Peterson, Lewis V. and Schramm, Wilbur},
+  year = {1954},
+  journal = {Audio Visual Communication Review},
+  volume = {2},
+  number = {3},
+  eprint = {30218399},
+  eprinttype = {jstor},
+  pages = {178--189},
+  publisher = {Springer},
+  issn = {0885-727X},
+  urldate = {2024-03-18},
+  file = {/Users/cbbcbail/Zotero/storage/VZNSGB7J/Peterson and Schramm - 1954 - How Accurately Are Different Kinds of Graphs Read.pdf}
+}
+
 @inproceedings{redmondVisualCuesEstimation2019,
   title = {Visual {{Cues}} in {{Estimation}} of {{Part-To-Whole Comparisons}}},
   booktitle = {2019 {{IEEE Visualization Conference}} ({{VIS}})},
@@ -530,7 +616,7 @@ @article{ventocillaComparativeUserStudy2020
 @article{vonhuhnFurtherStudiesGraphic1927,
   title = {Further {{Studies}} in the {{Graphic Use}} of {{Circles}} and {{Bars}}: {{A Discussion}} of the {{Eell}}'s {{Experiment}}},
   shorttitle = {Further {{Studies}} in the {{Graphic Use}} of {{Circles}} and {{Bars}}},
-  author = {{von Huhn}, R.},
+  author = {{von Huhn}, R. and Croxton, Frederick E.},
   year = {1927},
   journal = {Journal of the American Statistical Association},
   volume = {22},

partWhole.md

@@ -28,20 +28,88 @@ csl: ieee.csl
 
 [@croxtonBarChartsCircle1927]
 
+### Graphic Comparisons by Bars, Squares, Circles, and Cubes
+#### Croxton, 1932
+
+[@croxtonGraphicComparisonsBars1932a]
+
+### How Accurately Are Different Kinds of Graphs Read?
+#### Peterson and Schramm, 1954
+
+[@petersonHowAccuratelyAre1954]
+
+### A Study of Graph Comprehension Difficulties
+#### Culbertson and Powers, 1959
+
+[@culbertsonStudyGraphComprehension1959]
+
+### Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods
+#### Cleveland and McGill, 1984
+
+[@clevelandGraphicalPerceptionTheory1984]
+
+### Graphical Perception and Graphical Methods for Analyzing Scientific Data
+#### Cleveland and McGill, 1985
+
+[@clevelandGraphicalPerceptionGraphical1985]
+
+### Graphical Perception: The Visual Decoding of Quantitative Information on Graphical Displays of Data
+#### Cleveland and McGill, 1987
+
+[@clevelandGraphicalPerceptionVisual1987]
+
+
+### An Information-Processing Analysis of Graph Perception
+#### Simkin and Hastie, 1987
+
+* The authors conduct studies comparing bar, stacked bar and pie charts with two segments on proportion (the percentage of the segment relative to the whole), comparison (the percentage the smaller segment was of the larger), and discrimination tasks (the larger of the two segments). In the first experiment the subjects were given a 1 or half second viewing time and in the second experiment they answered at their own pace. As expected, the pie chart performed well for the proportion tasks while the bar chart performed well for the comparison and discrimination tasks. They then propose schematic summaries pairing their results with prior work to combine scanning, projection, superimposition, and detection operators to the three tasks and charts in the studies. They propose that the proportion task uses anchoring then scanning, comparison uses projection, then anchoring, then scanning for bar charts but requires superimposition, then anchoring, then scanning for the stacked bar and pie charts. The suppose that anchoring is the key process for the proportion task and pie charts salient 0, 90, 180 degree anchors support this well explaining the advantage. They claim that angles provide the least accurate estimates because of the inferior anchoring when not at perceptually salient angles.
+
+[@simkinInformationProcessingAnalysisGraph1987]
+
+### The Perception of Statistical Graphs
+#### Lewandowsky and Spence, 1989
+
+[@lewandowskyPerceptionStatisticalGraphs1989]
+
+### Displaying Proportions and Percentages
+#### Spence and Lewandowsky, 1991
+
+[@spenceDisplayingProportionsPercentages1991a]
+
 ### Save the Pies for Dessert
 #### Few, 2007
 
 * The author of this blog post describes the flaws of the pie chart and argues that they should not be included in a visualization design program. They state that the primary strength of the pie chart is that the part-whole relationship is built into it in an obvious way and that the only advantage of the chart is that it is superior for understanding the combined proportion of parts in a dataset based on the studies by Spence and Lewandowsky. He claims that a bar chart with a quantitative scale is only slightly less effective than a pie chart for a 25% segment and that pie charts are only effective in judging values at 0, 25, 50, 75, and 100 percent but that these values can be better visualized by a bar graph. He also claims that alignment is a significant aid in reading values from a pie chart. He notes that adding labels and values to a pie chart is equivalent to producing a poorly designed table and that a bar chart is a better visualization than either a table or a pie chart. He also notes that augmentations such as 3D effects, internal divisions, transparency and gloss are harmful to reading the charts. Finally he states that comparisons between pie charts are difficult and this task is much better served by bar, line, and area charts.
 
 [@fewPiesDessert2007]
 
+### Crowdsourcing graphical perception: using mechanical turk to assess visualization design
+#### Heer and Bostock, 2010
+
+[@heerCrowdsourcingGraphicalPerception2010]
+
+### Do Mechanical Turks dream of square pie charts?
+#### Kosara, 2010
+
+[@kosaraMechanicalTurksDream2010]
+
+### No Humble Pie: The Origins and Usage of a Statistical Chart
+#### Spence, 2005
+
+[@spenceNoHumblePie2005]
+
 ### Judgment Error in Pie Chart Variations
 #### Kosara, 2016
 
 * The authors conducted a study comparing four variations of pie charts to a standard pie chart acting and a control. The variations were an expanded slice, an exploded pie, an elliptical pie and a square pie. They find that all variations cause an increase in error including those that do not distort the central angle. They find no change in response time and are unable to show a difference between models for angle, arc, or area compared with the results. This supports the idea that all three methods are used in estimating values from pie charts.
 
 [@kosaraJudgmentErrorPie2016]
 
+### An Empire Built On Sand: Reexamining What We Think We Know About Visualization
+#### Kosara, 2016
+
+[@kosaraEmpireBuiltSand2016]
+
 ### Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts
 #### Skau and Kosara, 2016
 
@@ -62,3 +130,13 @@ csl: ieee.csl
 * The author conducted a series of studies comparing the performance of pie charts and horizontal stacked bar charts with various visual cues for estimating viewer estimation of part-whole relationships. The charts have two segments each and the viewer must estimate the value of the indicated part in the pie chart or the stacked bar chart. The findings show visual cues in stacked bar charts improve accuracy, pie charts outperform stacked bar charts, and that there is evidence of natural visual anchors in baseline pie charts that subjects are using with pie charts.
 
 [@redmondVisualCuesEstimation2019]
+
+### Circular Part-to-Whole Charts Using the Area Visual Cue
+#### Kosara, 2019
+
+[@kosaraCircularParttoWholeCharts2019]
+
+### The Impact of Distribution and Chart Type on Part-to-Whole Comparisons
+#### Kosara, 2019
+
+[@kosaraImpactDistributionChart2019]