Gross domestic product (GDP) is the standard measure of the value added created through the production of goods and services in a country during a certain period.
GDP is a famous and common measurement method. But does it has a real positive impact as it goes up?
Determining cause and effect is not a simple thing to do, but we can get a closer look at other important variables and comparate their correlation with GDP, to get a better understanding of this matter.
One of the interesting variables to look at is Life Expectancy, as it is the key metric for assessing population health.
So, with this in mind, this project aims to analyze the correlation between Life Expectancy and GDP to get a better understanding of the relationship between these two variables.
This project aims to analyze the correlation between GDP and Life Expectancy in six countries with different social, economic, and geographic realities.
Correlation is a statistical measure that expresses the extent to which two variables are linearly related (meaning they change together at a constant rate). It’s a common tool for describing simple relationships without making a statement about cause and effect.
The sample correlation coefficient, r, quantifies the strength of the relationship. Correlations are also tested for statistical significance.
Correlation can’t look at the presence or effect of other variables outside of the two being explored. Importantly, correlation doesn’t tell us about cause and effect. Correlation also cannot accurately describe curvilinear relationships.
If yes, go ahead and check out the "Correlation Between GDP and Life Expectancy.ipynb" file to see how the analysis was made and the possible conclusions.