Statistical adjustment in charts
Dec 05, 2011
On the book blog, I often talk about the reasons why statisticians adjust data, and why it is necessary in order to paint a proper picture of what the data is saying. (See here or here.)
On this blog, I have frequently complained about how the "prior information" on maps is too strong - large regions dominate our perception regardless of the data. In the U.S., large but sparsely populated states attain disproportionate attention.
So, why not bring "statistical adjustment" to maps?
That's exactly what cartograms do. For example, look at the following pair of maps created by the people at Leicestershire County Council. (PDF link here)
The map on the left and the cartogram on the right plot identical data. The only difference is that each hexagon on the cartogram represents an equal number of people. The two views give very different impressions: the big dark green patch on the middle-right of the map -- representing a relatively sparse neighborhood -- is shrunk to a single dark green hexagon on the cartogram. Meanwhile, the most deprived areas (dark purple) which look relatively small on the map are expanded to quite a few hexagons.
According to the map, most of the county live in areas ranked in the half considered less deprived (green), and that is good news. But wait... there is a lot of purple in the cartogram!
The real piece of news is that the majority of people live in the half of the neighborhoods considered more deprived (purple) but this uncomfortable fact is well-hidden in the mostly green map on the left.
Given that the measures of "deprivation" are about people, not geographical neighborhoods, the cartogram is much closer to the real world experience... notwithstanding the obvious geographical distortion introduced by the statistical adjustment.
According to Alex L., who is part of the team producing these graphics:
LSOAs were created for the 2001 [UK] Census to disseminate the data and are generally considered to represent 'neighbourhoods'. They are created to have a broadly consistent population (approx 1500 people in 2001) and socio-economic traits.
Question: Is there any reason to show the map at all?