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MSc Project · COMP11108 · Data Analysis & Visualisation

GDP vs Life Expectancy — Global 60-Year Analysis

Analysed World Bank data across 149 countries from 1960–2020 using Pandas, Seaborn, Matplotlib, and Plotly. Full pipeline: data cleaning, feature engineering, correlation analysis, and an interactive Plotly dashboard. Identified a strong positive correlation (r=0.74 in 1960, r=0.70 in 2020).

149
Countries
60yr
Time span
r=0.74
Correlation
85yr 70yr 50yr 1960 2020 Low GDP → High GDP
Overview

An MSc data analysis project (COMP11108) exploring the relationship between economic prosperity (GDP) and public health outcomes (life expectancy) across 149 countries and six decades of World Bank data (1960–2020).

Pipeline

Findings

A strong positive correlation between GDP and life expectancy held across the full 60-year period — r=0.74 in 1960, moderating slightly to r=0.70 by 2020, suggesting that while wealth remains strongly linked to health outcomes, other factors (healthcare access, public health policy) have grown in relative importance over time.

Why it's relevant

This project is the direct foundation for the planned 'Interactive Public Health Data Analytics Platform' — extending this static analysis into a fully interactive web application.

PythonPandasSeabornPlotlyWorld Bank
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