A couple of weeks ago I ranted about a bubble chart which attempted to illustrate trends in CDO issuance by large investment banks. If circles are a bad choice for depicting data, pictures of brains are even worse, but brains are what the BBC News designers settled on when it came to looking at the countries which have been most successful at winning Nobel prizes.

There is no doubt that the idea to link Nobel prizes to brains is an appealing one, but comparing the relative sizes of these blobs of grey matter is not easy. In fact, it’s hard to avoid simply reading the numbers rather than looking at the graphics, which rather defeats the purpose of charting the data. A simple league table would have done the same job.

This would come as no surprise to William Cleveland, a statistician who took an experimental approach to understanding the effectiveness of different graphing techniques. In Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods, published jointly with Robert McGill in 1984, Cleveland ranked our ability to judge variation in charts in the following order:

1. Position along a common scale
2. Positions along nonaligned scales
3. Length, direction, angle
4. Area
5. Volume, curvature
6. Shading, color saturation

Furthermore, Cleveland’s experiments used circles rather than brains when area perception was tested and I suspect, brains would fall somewhere between four and five. This perception ranking also points at a better choice of graphic: a simple bar chart, which relies on judgement of length rather than area. Better still, since the bars have a common baseline, comparing them in fact requires judgement of position along a common scale, the easiest of the perception tasks.

Top 5 Nobel Prize winning countries from 1901

The bar chart is much easier to read, but it may seem a little pedestrian to graphic designers excited by the idea of weaving in a brain image. While I am happy with the simple bar chart, sprucing it up with a background image does not interfere very much with the ease of reading the data. Here is an example, although I am sure those more adept at the use of Photoshop (or Gimp in this case) could come up with something better still.

The BBC post includes two more charts, which also have their shortcomings. The pie chart showing just how few women have won Nobel prizes is a particular waste of space. Certainly it is evident from the chart that women have not been awarded very many prizes, but simply stating in words that “the 41 of 806 prizes that went to women represent a mere 5.4%” does an even better job. Of course, the percentage could be added to the chart, but the necessity of adding a lot of numbers to a chart is a sure sign that the chart is not doing its job very well.

Possibly Related Posts (automatically generated):

• Pyramid Perversion – More Junk Charts (12 March 2010)
• Visualizing smoking risk (21 October 2010)
• Junk Charts #4 – Puns are dangerous (31 August 2010)
• Deceptive Charts #2 (20 November 2009)