The data is available for all countries as well according to specific regions. While country based data is available, regions based on formal and informal political and economic groups such as OECD and Sub Saharan Africa are also presented. The tool takes a 360 degree view of all the various economic and social factors that might shape the world. Hence, there are several indicators ranging from income based indicators (GDP per capita , GDP USD based on Purchasing Power Parity etc.) (Gapmider, 2018)
Additionally, it is interesting to see Math Achievement as an indicator for education. Interestingly, the countries that ranked the highest in the 4th Grade achievement are dispersed all over the world such as the African Continent (Morocco , Tunisia), Oceania (New Zealand), Eastern Europe (Ukraine, Georgia), Middle east Region Iran, United Arab Emirates). Based on a simplistic prima facie observation, this indicator might be the most well dispersed indicator available on the tool. (Gapmider, 2018)
The countries with the highest child mortality rate are the countries with the highest rate per woman. There is a direct and a corresponding relationship between the countries that show the highest presence of the above two variable. Some of the countries that feature highly in the indicator “ number of babies per woman” also, feature highly on the indicator of “ Child Mortality” . For example, Niger, Somalia, Chad are countries that feature highly on both indicators. Hence, it is easy to say, based on a prima facie observation data presented, without conducting any other analysis that Child Mortality is directly related to the number of babies born to a woman in any given country. (Gapmider, 2018)
An interesting observation is that all the top ten countries on both these indicators are from the continent of Africa. (Gapmider, 2018)
- Technically, Seychelles has the highest GDP per capita at 27, 000 USD. However, for this comparison, the comparison between Mauritius and Equatorial Guinea seemed ideal. Both countries have GDP of 21, 000 USD per capita and 20,500 per capita respectively. From an informal assessment based on the size of the bubble (the bubble is as large as the population), it would seem that the population size is roughly similar. Hence, the X-Axis was changed to reflect the number of babies per woman. The number of babies per woman for Equatorial Guinea was considerably higher than for Mauritius. It is established in the previous section that this is a direct relationship between Child Mortality and number of babies per woman of a country. Hence, one of the possible causes for this discrepancy could be the number of babies born per woman. (Gapmider, 2018)
- According to the Gapminder Data, the income for many countries takes a dive in the year 1918. (Gapmider, 2018) It is common knowledge that 1918 was the year the World War started as well as the Flu epidemic came about. Hence, both causes were examined. The World war however, did not start until November and most countries did not participate in World War 1. The Great Influenza Outbreak of 1918, however, has been known to have caused the death of over 40 million people world wide. (Kolata, 2001). This could have affected the overall life expectancy of many countries of the World.
The Line chart was used for this assessment as it it the only chart that is available in the Log form as well as the linear form. (Gapmider, 2018) Generally, the Log form graphs are plotted on the logarithmic scale and the difference between the as percentages while the linear ones are plotted according to absolute differences while the linear scale utilizes the absolute values to see the plot the changes. Hence, the logarithmic Scalre data points tend to be closer. (Smyth, 2005)
Gapmider. (2018, June). Gapminder Offline Tool. Retrieved from Gapminer: https://www.gapminder.org/data/
Kolata, G. (2001). Flu: The Story Of The Great Influenza Pandemic of 1918 and the Search for the Virus That Caused it. New York: TouchStone.
Smyth, T. (2005, October 06). Linear vs logarithmic scales. Retrieved from Computing Science, Simon Frasier University: https://www.cs.sfu.ca/~tamaras/digitalAudio/Linear_vs_logarithmic.html