Graphical Integrity

"The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the quantities represented." -Edward Tufte

It is amazing how easy it is to find highly inaccurate and misleading data graphics and charts even in this year 2019. These inaccuracies and sometimes outright perversions of the truth are of particular concern to an insta-culture who gets its news in headlines, memes, charts and other bite-sized generalizations via social media and rarely looks for the evidence beyond the headlines and the source data behind the charts.

The “Lie Factor”, first defined by American statistician Edward Tufte is defined as "a value to describe the relation between the size of effect shown in a graphic and the size of effect shown in the data." A larger Lie Factor value indicates a higher level of deception or "inaccurate scaling/weighting".


Lie Factor in Action:

The numbers do not equate to the scale of the bars and money bags... not quite as "strong" as projected.

This example mixes 2 different scales and data sets and only serves to confuse the reader...

This is a propaganda data graphic displaying a series of 5 increases using a totally nonsensical scale

This graphic shows Last Year, Last Week, and Current Week as having the same temporal scale.... O'Lie Factor.

Lie Factor Breakdown:

Lie Factor is the change shown in the graphic (say 100%) divided by the change reported in the data (say "50%") - (100/50 = a LF of 2)

There are reasons for misleading graphics that go beyond propaganda and sensationalist news articles:

• Lack of quantitative skills on the part of the graphic creator and publication editor
• Doctrine that statistics are boring and therefor need to be "jazzed up"
• Doctrine that graphics are only for unsophisticated and so don't need "accuracy constraints"
• Failure to treat graphics with the same fidelity to the truth as the written word it accompanies

Other ways that graphical information displays are corrupted include cherry-picking data, making small changes appear large by showing a small scale interval and when all else fails for information manipulators- using fake data.

It is important to not jump to conclusions when assessing graphical information displays even if it is coming from a reputable publisher. As you can see it is not always obvious that the information being communicated graphically is accurate. Wherever possible, get a look at the source data.

"When we see a chart or diagram, we generally interpret its appearance as a sincere desire on the part of the author to inform. In the face of this sincerity, the misuse of graphical material is a perversion of communication, equivalent to putting up a detour sign that leads to an abyss" - Wainer

References:

https://viz.wtf/

https://infovis-wiki.net/wiki/Lie_Factor