Juhi Bhandari
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    5 min read·Project·Project

    GDP vs Life Expectancy Analysis

    Cleaned multi-year datasets and ran regression analysis across six countries to find what actually drives life expectancy.

    Team: Academic ResearchTools: SPSS, Tableau, Excel
    6
    Countries
    Multiple
    Variables
    Decision-ready
    Insight

    TL;DR

    • Problem: Everyone says GDP drives life expectancy. The real finding was where and why that relationship breaks down.
    • Decision: Ran correlation, hypothesis testing, and regression modeling across six countries.
    • Result: Proved that GDP-life expectancy relationship varies significantly and healthcare quality changes the story entirely.

    Context

    Public data on GDP and health outcomes is widely available but rarely interrogated properly. This project asked a sharper question.

    Problem

    Generic claims about GDP and health ignore the variables that actually shift outcomes - healthcare quality, education, unemployment, and political stability.

    What I Did

    Cleaned and normalized multi-year datasets across six countries. Ran correlation analysis, hypothesis testing, and regression modeling in SPSS. Built Tableau visualizations to communicate findings clearly.

    Results

    Proved that the GDP and life expectancy relationship varies significantly by country and that healthcare quality and education levels change the story entirely.

    Learnings

    The best analytical insight is not the obvious one. It is the one that changes what decision you make next.

    Artifacts

    SPSS regression output, correlation matrix, hypothesis test results, Tableau visualizations, cleaned multi-year dataset.