Yaw Assensoh Opoku

Global Development Trends Analysis

Economic Indicators & Country Development Metrics

Presentation board on a tripod stand displaying various colorful data visualizations including line charts, bar graphs, pie charts, and area charts. The board is set against a muted blue background, suggesting a professional and analytical environment. No visible text is present. The tone is focused and data-driven.

Project Overview

Goal:

Analyze global development data to identify patterns, economic trends, and correlations between development indicators across 200+ countries.

Business Problem:

Provide data-driven insights for policymakers, NGOs, and international organizations to make informed decisions about resource allocation and development strategies.

My Role & Process:

  • Data Collection & Integration: Aggregated data from World Bank, UN, and global health databases
  • Exploratory Analysis: Analyzed correlations between economic, health, and education indicators
  • Regional Analysis: Identified patterns across different geographic regions and income levels
  • Insights Generation: Created predictive models and strategic recommendations for development planning

Data Analysis & Visualizations

Linear Regression: GDP vs Life Expectancy

GDP vs Life Expectancy

Linear regression analysis showing the relationship between GDP per capita and life expectancy.

Key Finding: 0.000208 coefficient indicates that for every $1,000 increase in GDP per capita, life expectancy increases by approximately 0.2 years.

Correlation Matrix Heatmap

Variable Correlations

Heatmap showing relationships between key development indicators.

Key Finding: Strong positive correlation 0.70 between internet usage and life expectancy, suggesting digital access may impact health outcomes.

Line chart showing global average internet usage growth percentage from 2000 to 2025. The chart features a sharp spike in growth around 2013, reaching nearly 500 percent, then a steady decline in growth rates through 2025. The x-axis is labeled Year and the y-axis is labeled Internet Growth percent. The chart title reads Global Average Internet Usage Growth percent. The setting is clean and analytical, focused on data trends. No other text is present. The tone is neutral and informative.

Internet Usage Growth

Trend analysis of global internet adoption over time.

Key Finding: Rapid growth in internet usage with a 500% increase from 2000 to 2025, indicating accelerating digital transformation.

Elbow Method for Clustering

Country Clustering Analysis

Elbow method and silhouette scores for determining optimal country clusters.

Key Finding: Optimal clustering at k=4 with silhouette score of 0.46, suggesting four distinct development groups among nations.

Analytical Insights

  • Economic-Health Relationship: The regression model (y = 67.70 + 0.000208 * GDP) explains how economic prosperity correlates with longer life expectancy, with diminishing returns at higher GDP levels.
  • Digital Divide Impact: The strong correlation (0.70) between internet usage and life expectancy highlights the importance of digital infrastructure in development strategies.
  • Development Trajectories: Cluster analysis reveals four distinct country groups with different development patterns, enabling targeted policy interventions.
  • Growth Dynamics: Internet adoption has grown exponentially, suggesting technology as a key driver in recent development progress.

Key Findings & Impact:

200+
Countries Analyzed
Comprehensive global coverage
Strong
Correlation Found
Internet access & life expectancy
4
Country Clusters
Distinct development patterns

Strategic Insights:

  • Identified strong correlation between internet access and health outcomes (r=0.70)
  • Quantified GDP impact on life expectancy with predictive regression model
  • Segmented countries into 4 development clusters for targeted interventions
  • Documented exponential growth in internet adoption as development accelerator
  • Provided data-driven recommendations for international development strategies

Tools & Technologies:

Python
Data Analysis & Modeling
SQL
Data Aggregation
Tableau
Interactive Dashboards
Jupyter
Analysis & Documentation

Data Sources:

World Bank Open Data UN Development Programme Global Health Observatory National Statistics
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