Analysis of Worldwide Life Expectancy in the period between 2000 and 2015 Based on Statistical Regression Method

This project focuses on exploring the relationship between life expectancy and the factors that may influence it across all countries in the world between 2000 and 2015. The core question here is “Which factors affect life expectancy most?”. We used the dataset provided by World Health Organization (WHO), which can indicate its authenticity, and we used both dropping and replacement methods to eliminate the null values in it. After pre-processing, two methods of feature selection were applied: Mutual Information and Boruta, which led to conclusions about which factors have the greatest impact on life expectancy. Regression models were then used on the well-processed dataset, and we analyzed their results to answer the questions in context. In the above processing and analysis, criteria (e.g. R2 score) that measure the dataset and the performance of models have been observed and visualizations have been implemented. It is believed that the project will help to formulate policies that a country should implement accordingly in order to effectively increase the life expectancy of its people.