Finding stories in datasets – Gapminder Income Chart

Life Expectancy vs Income - a chart by Gapminder.org
Life Expectancy vs Income - a chart by Gapminder.org

From looking at the dataset on the Gapminder income chart, it can be concluded that the higher the income that a country has, the higher the life expectancy for a country will be. Norway and Brunei for example, have an average income of around 64-76k(ppp$) per person a year which is on the higher end of the scale. The life expectancy for these two countries ranges between 77.4-82.4 years. Somalia and Congo however, earn around 629-721(ppp$) and have a lower life expectancy of 58-62.4 years. 

The gapminder chart also determined that most of the countries that have a high population, will collectively have a lower income than countries with a lower population. For example, China has a population of around 1.42 billion, yet the average person earns only 16k(ppp$) a year. The US has a population of around 327million and the average citizen bring home 54.9k(ppp$) a year. Ireland has only 4.8million people yet they earn 65.6k(ppp$) on average, a year and Luxemborg is home to only 590k people and the average person earns around 99k(ppp$) a year.  

The story I have chosen to develop is the population vs income case. I think that this dataset, is quite interesting as most people would believe that as countries with a higher population tend to be a lot more developed and advanced, they would earn more money from their work. The data gathered proves that this is not the case and could therefore create the following story of smaller countries having a more economical and wealthy society than bigger countries.