Juhi Bhandari
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    5 min read·Project·Project

    World University Rankings Analysis

    Applied regression and ANOVA across 2200 universities to prove faculty quality is the strongest ranking predictor.

    Team: Academic ResearchTools: SPSS, Tableau
    53.2%
    Variation Explained
    2,200
    Universities
    ANOVA
    Methods

    TL;DR

    • Problem: What actually drives a university's global ranking? Analyzed 2200 universities to find out.
    • Decision: Ran descriptive statistics, correlation, ANOVA, and regression modeling across 2200 universities.
    • Result: Model explains 53.2% of university score variation. Faculty quality has the highest impact.

    Context

    University rankings shape policy, funding, and student decisions globally. Understanding what drives them has real strategic value.

    Problem

    Rankings feel like a black box. Institutions invest in the wrong areas because they do not know which variables actually matter.

    What I Did

    Ran descriptive statistics, correlation analysis, ANOVA, and regression modeling across 2200 universities using SPSS. Built Tableau dashboards to visualize faculty quality versus score and global university distribution.

    Results

    Model explains 53.2% of university score variation. Faculty quality has the highest impact, making it the clearest lever for institutions to pull.

    Learnings

    Good analytics does not just describe the data. It tells you where to invest next.

    Artifacts

    SPSS descriptive statistics, ANOVA results, regression model, Tableau dashboards, faculty quality analysis.