I investigated CO2 emissions in terms of per capita output – China vs. US. In Gapminder “graph menu” this appears as a specific subtopic – “US vs. China – who emits the most CO2?”. Use x-axis = Time, and y-axis = CO2 emissions; select only US and China in the country option menu. By tracking CO2 emissions over time for these 2 countries, we observe that although both countries emit progressively more CO2 from 1820 to present, the trajectories of change are quite different. For the US, per capita emissions gradually increase over time. However, China’s per capita emission rate stays relatively stable until very recently. The graph is: www.bit.ly/zCKw1q, but you must play the time series to observe the pattern.
I then changed the x-axis to “Literacy rate, Adults 15 yrs +”. Find this option by first selecting “Education” in the dropdown menu. This brings up a dataset for multiple countries. A cursory analysis suggests – in order to keep CO2 emissions low, we should discourage education! 🙂
Potential follow-up questions for students include: what are some advantages/disadvantages of viewing the data in this way? What is the next question you would ask of the dataset? Do you expect the same trends? Why/why not?