Introduction

The data that were utilized in this analysis were taken from Gapminder. The main variables that were used were Life Expectancy, the average amount of years a person in that country is predicted to live and gross domestic product per capita.

Abstract

To create the models, both of the variables had to be modified. The first variable that was edited was GDP per capita. Due to to Kuwait having a GDP per capita almost two times as high as all of the other countries, due to small but rich population, it had to be removed from the dataset. Additionally, a log10 of the income variable was utilized in order to capture the variance between the richest and poorest nations. The other variable Life Expectancy, also had to have two outliers removed, which were Rwanda and Afghanistan which had the lowest life expectancy values compared to the other countries in this dataset, well below world average at the time.

GDP-percap and life exp. per country

Using geom_bind per each continent

Chart using geom_bin2d

Geom_bind with different color scale

Chart using geom_hex

Improvements from previous version

We added a facet for each continent represented in the dataset, as well as we changed the color scale of the geom chart, using colors that distinguish each observation from others in the chart, with that modification there is no need to add a density to notice where the most concentrated areas are at, instead we can see them by the green color.