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Life Expectancy Analysis Project

Overview

Life expectancy varies significantly across countries due to a complex combination of socioeconomic, healthcare, environmental, and educational factors. This project aims to analyze the key determinants of life expectancy, identifying how different variables influence longevity across regions and countries. By exploring these factors, we can gain valuable insights into disparities in global health outcomes and identify trends and patterns over time.

Objective

The primary goal of this project is to identify and analyze the factors that contribute to life expectancy differences across countries. Specifically, we aim to address the following key research questions:

Research Questions:

Which region and country currently has the lowest average life expectancy, and what factors contribute to this? Which country has the highest life expectancy, and what are the underlying reasons for its longevity? Has life expectancy been increasing over time, and is this trend consistent across all countries? What are the key factors influencing life expectancy across different countries?

Data Sources

This project utilizes publicly available datasets that contain socioeconomic, environmental, and healthcare indicators for various countries. The dataset is available on kaggle https://www.kaggle.com/datasets/kumarajarshi/life-expectancy-who

Key Steps

Data Collection: Collect life expectancy and related socioeconomic and healthcare data from various sources.

Data Cleaning: Handle missing values, inconsistent data types, and perform any necessary data transformation.

Exploratory Data Analysis (EDA): Perform descriptive statistics and visualizations to understand trends, correlations, and outliers.

Modeling: Use regression models (Random Forest) to identify the key factors influencing life expectancy.

Conclusion & Insights: Summarize the findings, identify the strongest predictors of life expectancy, and provide policy recommendations.

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