The configuration I set for my graph was plotting income vs. child mortality over the past 100 years, from 1918 to 2018. The income was set for the x axes and the child mortality was set for the y axes. The income was in terms of per person (GDP/capita, PPP$ inflation-adjusted) and the child mortality was in terms of 0-5 year-olds dying per 1000 born. I also set the size of the bubbles to represent the population of the country.
I notice that in 1918, the child mortality rate for everyone had a much smaller range than the income for everyone. It was interesting to see that countries in Africa all had very similar rates of child mortality but had a rather wide range of income. As time progressed, countries began to move downwards and to the right, indicating a negative relationship between child mortality and income. In other words, as time progressed, child mortality decreased and income increased. Generally, the countries with highest income and lowest child mortality were from North America and Europe, followed by Asian and then Africa. I noticed that as time progressed, there was not as much of a distinction. Something interesting that I saw was that in 1918, there were not many outliers, but in the 60s and 70s there were several, specifically Asian countries and specifically with high incomes. I was a little surprised to see just how big China and India were when compared to the rest of the world. I noticed that countries near the top of income and bottom of child mortality tended to move steadily, whereas countries behind them were more sporadic and unpredictable. While this may seem obvious, I think it’s important to mention that income was the variable that was liable to experience the most change, whereas population and child mortality had much more steady paths towards their directions.
The positive trend of income reflects Rosling’s TedTalk where he talked about how the income of countries had gradually increased, although it was not always steady. As mentioned by West, it’s important to understand that correlation does not mean causation. While it’s possible to suggest that an increase in income will lead to a decrease in child mortality, an increase in population will lead to an increase in income, or any other combination that can be made, there are many other factors that are influential and that are outside the illustration provided by the chart. I think that improvements in technology has improved across the globe, which would improve knowledge and healthcare and is shown through the general decrease in child mortality.