Review: Gapminder 3
Nov 30, 2005
The next chapters of Gapminder take the scatter plot of income and child mortality further.
V. Income and health of countries
Concept used: standard deviation, measure of location and of dispersion
Highlight: this chapter is an amazing illustration of why it is dangerous to look at only averages but not dispersion. The screen shot on the left shows that Mauritius is nothing like the rest of Africa in terms of income or of child survival rate.
Alert readers will notice that Gapminder has switched the y-axis from child mortality to child survival, which is significantly easier to grasp even though the data is the same. (Did they read Hadley's comment?)
Food for thought: 1) The labeling of the log scale for child survival rate may confuse some. 2) The population size dimension as rendered in bubbles interferes with our understanding of the correlation between GDP per capita and child survival while adding little if any value.
Presumably, population size is shown so that the reader can observe the correlation between population and GDP per capita, and that between population and child survival. The reader can judge for themselves whether the bubble chart is effective in presenting such correlations (see charts below).
3) The log-log scale can easily mislead us in judging the magnitude of dispersion. Even though the countries in OECD (aquamarine bubble) look relatively less dispersed, in reality, this may not be so because small distances on the right side of the page must be translated conceptually to large distances (to reverse the log scale).
VI. Same Income, Different Health
Concepts used: scatter plot
Highlight: This chapter is a tour de force in explaining how to read scatter plots. Besides, it proves how animation can significantly improve instruction. The screen shot on the left is but one example.
VII. Development directions
VIII. Differences within countries
We discussed development paths last time. Chapter 8 drills down further into distributions within countries; its only disappointment is the lack of data, especially for OECD countries (wanting to hide social inequality?)
This is an all-around fantastic effort to bring color to the voluminous data in the Human Development Report. Many important statistical concepts are included and carefully explained (histograms, means and dispersion, different levels of analysis, scatter plots, etc.). In some cases, the choice of graphical construct exposes its limitation. What's more, the producers apparently are open to feedback; I have detected some improvements already and a Chapter 9 has appeared after I completed my review. Here are my reviews of earlier chapters.
Chapter 4 (touching on 7)