As developed nations around the globe focus on implementing sustainable energy sources to reduce their carbon footprint, studies have revealed an increase in carbon emissions in developing countries in relation to their human development index. This project aims to analyze the correlation between carbon emissions and human development index through exploratory data analysis.
R programming language in RStudio was used to conduct this analysis, incorporating data from 1990 to 2017 on carbon emissions per capita, sector, source, and human development index. The countries were divided into three groups based on their human development index, with a threshold of 0.8 defining high-level countries. The dataset was subjected to linear regression, ANOVA, Kruskal Wallis, Shapiro Wilks normality test, and Spearman's correlation test.
The results of the Spearman's correlation test show a significant relationship between human development index and carbon emissions in low-level countries. The heat and electricity sectors contribute the highest carbon emissions in high and middle-level countries, while the transport sector takes center stage in low-level countries. Furthermore, the research indicates that the human development index alone does not fully account for the variations in carbon emissions per capita, necessitating the inclusion of other factors such as population, health outcomes, and income in future research.