This project presents a statistical analysis of New York State's Tuition Assistance Program (TAP) across SUNY, CUNY, and private institutions. Using over 260,000 real-world records, we explored funding differences by income level, age group, dependency status, and sector type.
- 🧾 Dataset: 259,983 rows across 23 academic years
- 🧠 Methods: T-tests, ANOVA, Chi-square, Linear Regression
- 🧰 Tools: Python (pandas, matplotlib), LaTeX (report), Tableau (visuals)
STAT_Project_Report.pdf→ Final project reportProject_Code.ipynb→ Python notebook with full analysisTAP.csv→ Cleaned datasetReport_Latex_code.tex→ LaTeX source for report
- Atharv Kadam
- Rahul Ganesan
- Dnyaneshwari Rakshe
MS Data Science – University of Colorado Boulder