Sufficiency

4 posts
A pretty good chart ruined by some naive analysis

The following chart showing wage gaps by gender among U.S. physicians was sent to me via Twitter: The original chart was published by the Stat News website (link). I am most curious about the source of the data. It apparently came from a website called Doximity, which collects data from physicians. Here is a link to the PR release related to this compensation dataset. However, the data is not freely...

0 0
Round things, square things

The following chart traces the flow of funds into AI (artificial intelligence) startups. I found it on this webpage and it is attributed to Financial Times. Here, I apply the self-sufficiency test to show that the semicircles are playing no role in the visualization. When the numbers are removed, readers cannot understand the data at all. So the visual elements are toothless. Actually, it's worse. The data got encoded in...

0 0
Counting the Olympic medals

Reader Conor H. sent in this daily medals table at the NBC website: He commented that the bars are not quite the right lengths. So even though China and Russia both won five total medals that day, the bar for China is slightly shorter. One issue with the stacked bar chart is that the reader's attention is drawn to the components rather that the whole. However, as is this case,...

0 0
A Tufte fix for austerity

Trish, who attended one of my recent data visualization workshops, submitted a link to the Illinois Atlas of Austerity. Shown on the right is one of the charts included in the presentation. This is an example of a chart that fails my self-sufficiency test. There is no chance that readers are getting any information out of the graphical elements (the figurines of 100 people each). Everyone who tries to learn...

0 0
Scorched by the heat in Arizona

Reader Jeffrey S. saw this graphic inside a Dec 2 tweet from the National Weather Service (NWS) in Phoenix, Arizona. In a Trifecta checkup (link), I'd classify this as Type QV. The problems with the visual design are numerous and legendary. The column chart where the heights of the columns are not proportional to the data. The unnecessary 3D effect. The lack of self-sufficiency (link). The distracting gridlines. The confusion...

0 0