Impact of Gender and Race in Education Attainment in New York

Amir Jaraysa

Co-Presenters: Ummu Yuzugulluer

College: The Dorothy and George Hennings College of Science, Mathematics and Technology

Major: Computer Science

Faculty Research Mentor: Ching-yu Huang

Abstract:

This research explores the relationship between race, gender, and educational attainment in New York. The primary goal is to determine whether race or gender significantly influences the highest level of education achieved. Understanding these relationships can provide insights into potential socioeconomic disparities and inform educational policy decisions.The dataset, uscities_2024, contains demographic and educational information, specifically focusing on individuals in New York. The dataset consists of 5163 records and includes five attributes: Gender, Race, Education Level, City, and State (filtered to NY). The raw data presents categorical variables requiring preprocessing techniques such as encoding.To uncover meaningful patterns, we will apply ETL (Extract, Transform, Load) processes to retrieve data related to New York, convert categorical data into numerical format, remove duplicates and handle missing values, and store the cleaned dataset in a structured format before implementing K-means clustering to identify groups with similar educational attainment. Correlation analysis will assess relationships between race, gender, and education, while multiple linear regression will evaluate the predictive power of these attributes on education level.This study aims to find disparities in educational attainment across racial and gender groups, with certain demographics achieving higher education levels at different rates. These insights could highlight systemic factors affecting education in New York, offering valuable implications for policymakers and educators.