wicked_problems

Pick at least one configuration (life expectancy vs income in the UK and Cuba over the pat 80 years, for example). Try any combination(s) you like (no wrong answers here). Write what data you are displaying. Write about what you see or what surprises you, if anything. As best you can, connect what you see to ideas in previous readings from Rosling, West, Sen, another course, or from your experience.

On the Gapminder site I compared CO2 Emissions with income. The site didn’t assign the actual correlation but it appear there was some kind of exponential growth in CO2 Emissions lining up with a higher income. I was surprised to see such a strong curve in the graph, but upon further considering the factors in CO2 Emissions it makes sense that countries with higher income likley have more factors and production and overall polutants. This connects with one of West’s sentiments that as one thing grows (i.e. a city) both positive effects and negative effects tend to stem from it.

Another combination of variables I found interesting was Babies per woman and population. I would’ve expected that countries with women having more babies on average would potentially have a higher population but it seems that babies per woman could also be linked with life expectancy and education and a variety of other aspects because the two are not linked. Rosling would certainly have something to say about the “us” and “them” mentality arising between countries having much higher average babies per woman. This is because they’re nations with roughly equivalent populations as many wealthy countries that have lower average babies which is showing for mortality rate in them and many other factors, yet they aren’t so different from wealthy countries in size.

Lining up extreme poverty and babies per woman yields a somewhat logarithmic curve. While obviously there is a much wider variety of variables impacting the countries with higher amounts of average babies, there appears to be a link between the two axes. This suggests that either having a lower average amount of babies and the effects leading to it can help predict a lower level of poverty in society and potentially vice versa. This is also an example of a graph that definitely has more too it than just the plotted variables so conclusions or causations cannot be strictly drawn. I wasn’t expecting this particular logarithmic shape because it seems to say that after a country’s average babies passes about 4 they are likely dealing with similar poverty levels to the countries with even higher averages.

I compared overall happiness score and pump price for gasoline too, but there was no correlation.