📉Graphical Representation: Things to Avoid (Just the Quotes)

Disclaimer: the following quotes are intended as a list of the things to avoid in Graphical Representation. For the full quotes see the previous post

"[...] avoid complicating the diagram by including too much data." (Armand Julin, "Summary for a Course of Statistics, General and Applied", 1910) 

"In general, the comparison of two circles of different size should be strictly avoided." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)

"Try telling the story in words different from those on the charts. […] If the chart shows a picture, describe the picture. Tell what it shows and why it is shown. If it is a diagram, explain it. Don't leave the audience to figure it out." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2" (5), 1948)

"It is not enough to avoid outright falsehood; one must be on the alert to detect possible distortion of truth." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"[...] avoid distortion or misrepresentation." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"The designer normally should place no more than three data paths on the graph to prevent confusion - particularly if the data paths intersect at one or more points on the Cartesian plane." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)

"There are two kinds of misrepresentation. In one, the numerical data do not agree with the data in the graph, or certain relevant data are omitted. This kind of misleading presentation, while perhaps hard to determine, clearly is wrong and can be avoided. In the second kind of misrepresentation, the meaning of the data is different to the preparer and to the user." (Anker V Andersen, "Graphing Financial Information: How accountants can use graphs to communicate", 1983)

"Do not allow data labels in the data region to interfere with the quantitative data or to clutter the graph. […] Avoid putting notes, keys, and markers in the data region. Put keys and markers just outside the data region and put notes in the legend or in the text." (William S Cleveland, "The Elements of Graphing Data", 1985)

"Make the data stand out and avoid superfluity are two broad strategies that serve as an overall guide to the specific principles. " (William S Cleveland, "The Elements of Graphing Data", 1985)

"Shorten long labels; avoid abbreviations unless they are universally understood; avoid repetition on the same graph." (Mary H Briscoe, "Preparing Scientific Illustrations: A guide to better posters, presentations, and publications" 2nd ed., 1995) 

"[...] avoid those graphical features that are purely decorative [...]" (Phillip I Good & James W Hardin, "Common Errors in Statistics" (and How to Avoid Them)", 2003)

"[...] avoid useless graphics." (Jacques Bertin [interview], 2003)

"If a break cannot be avoided, use a full scale break." (Naomi B Robbins, "Creating More effective Graphs", 2005)

"[...] when labels abandon the data points, then a code is often needed to relink names to numbers. Such codes, keys, and legends are impediments to learning, causing the reader's brow to furrow." (Edward R Tufte, "Beautiful Evidence", 2006) [argumentation against Cleveland's recommendation of not using words on data plots]

"Generally pie charts are to be avoided, as they can be difficult to interpret particularly when the number of categories is greater than five." (Jenny Freeman et al, "How to Display Data", 2008)

"Spurious precision should be avoided although when certain measures are to be used for further calculations or when presenting the results of analyses, greater precision may sometimes be appropriate." (Jenny Freeman et al, "How to Display Data", 2008)

"The data [in tables] should not be so spaced out that it is difficult to follow or so cramped that it looks trapped. Keep columns close together; do not spread them out more than is necessary." (Dennis K Lieu & Sheryl Sorby, "Visualization, Modeling, and Graphics for Engineering Design", 2009)

"[...] it is often best to avoid round charts and graphs." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"Avoid countering conventions where possible in order to avoid creating cognitive dissonance, a clash of habitual interpretation with the underlying message you are sending." (Noah Iliinsky & Julie Steel, "Designing Data Visualizations", 2011)

"The unseen data may be just as important, or even more important, than the seen data. To avoid survivor bias, start in the past and look forward." (Gary Smith, "Standard Deviations", 2014)

"Highlighting one aspect can make other things harder to see one word of warning in using preattentive attributes: when you highlight one point in your story, it can actually make other points harder to see. When you’re doing exploratory analysis, you should mostly avoid the use of preattentive attributes for this reason." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Collecting data through sampling therefore becomes a never-ending battle to avoid sources of bias. [...] While trying to obtain a random sample, researchers sometimes make errors in judgment about whether every person or thing is equally likely to be sampled." (Daniel J Levitin, "Weaponized Lies", 2017)

"[...] avoid pure colors that are bright and saturated." (Kate Strachnyi, "ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color", 2023)