Scholarship Impact Analysis (StudyGroup)

Project Overview

A data analytics case study investigating the impact of scholarship discounts on student enrolment using exploratory data analysis (EDA), statistical hypothesis testing, regression analysis, and data visualisation.

Executive Summary

Scholarship programmes represent a significant financial investment for educational institutions, yet their effectiveness is rarely evaluated using data.

This project analyses historical student application data from StudyGroup to determine whether scholarship discounts influence student enrolment and academic progression.

Using Python and statistical hypothesis testing, the analysis identifies the true impact of scholarship incentives and provides evidence-based recommendations for optimising future scholarship allocation.

Business Objectives

• Evaluate the impact of scholarship discounts on student enrolment.
• Determine whether discounts influence student progression.
• Analyse scholarship allocation across regions.
• Identify opportunities to improve scholarship investment.

Technology Stack

Project Workflow

Statistical Validation

Rather than relying solely on descriptive analytics, this project applies a Chi-Square Test of Independence to determine whether scholarship discounts have a statistically significant relationship with student enrolment and progression.

Conclusion — 1. Positive correlation between a student receiving a discount and enrollment. 2. No relationship between a student receiving a discount and progressing from the course.

Results

Key Finding

Scholarship discounts significantly influence student enrolment, but they do not have a statistically significant effect on student progression.

Results & Insights

1. Scholarships Increase Student Enrolment

Students receiving a scholarship discount were over 11× more likely to enrol than students who received an offer without financial support.

Comparing Conversion rate of students with an offer

With Discount, Without Discount

2. Regional Analysis

Recommendation

Adopt region-specific scholarship strategies rather than a uniform global allocation model.

3. Area-Level Analysis

The results indicate that scholarship decisions should be informed by historical conversion rates and regional performance, enabling resources to be directed towards markets where scholarships have demonstrated the greatest impact on enrolment.

Business Recommendations

• Optimise scholarship allocation based on historical enrolment conversion rates.
• Prioritise scholarship investment in regions with consistently high conversion performance.
• Review scholarship strategies in low-performing regions to improve return on investment.
• Consider additional factors influencing enrolment, such as programme demand, tuition fees and market conditions, alongside scholarship incentives.

Competencies Demonstrated

• Data Cleaning & Preparation
• Exploratory Data Analysis (EDA)
• Data Visualisation
• Chi-Square Hypothesis Testing
• OLS Regression Analysis
• Data-Driven Decision Making
• Technical Reporting

Project Impact

This analysis provides StudyGroup with a data-driven framework for evaluating scholarship effectiveness.

The findings demonstrate that scholarships are highly effective at improving student enrolment, while offering little measurable benefit to academic progression. These insights enable more strategic allocation of scholarship funding and support evidence-based decision-making.