Explore the data science projects created during Fall 2024, showcasing how our students harnessed data to solve real-world problems and uncover meaningful insights.
Durham and NC Police Stops: A Racial and Criminological Analysis
by Fasih Zulfiqar, Genevieve Jean-Pierre, Shotaro Okubo, Youngjo Min, Mark Horton, Tianyuan Du
[PDF]
Understanding the Factors Behind Suicide: A Data-Driven Approach
by Ritik Agrawal, Sasha Cui, Weihang Guo, Selina Zhan, Yixin Zhang
[PDF]
A Statistical Guide to Understanding NCAA March Madness
by Anika Mitra, Daniel Monyak, Dav King, Pedro Mello, Reina Kobayashi
[PDF]
COVID-19 Effect on Student Performance
by Anubhav Dhakal, Nick Li, Sihan Lyu, Hung Anh Vu, Yiqing Wang
[PDF]
Predicting NBA Player Score with Stats
by Zhengran Ji, Peter Min, Gangming Shao, Zhongming Zuo, Junyuan Deng
[PDF]
Building Competitive Football Teams: A Data-Driven Approach with Predictive Modeling and Clustering
by Bharat Kashyap, Jasmine Liu, Malika Syzdykova, Niharika Mylabathula, Zhaotian Wang, Zhe Han
[PDF]
Data-Driven Discoveries in Pet Adoption Patterns
by Yushan Shi, Yuqi Su, Mingxin Liu, Yurui Wu
[PDF]
Analyzing Trends in Mental Health Data Beginning with the Onset of the COVID Pandemic
by Jabari Kwesi, Furong (Flora) Jia, Zhujun Yao, Chloe Zhu, Jessie Cao
[PDF]
Predicting UFC Fight Outcomes: What Factors Matter Most?
by Rafael Alves, Sydney Lester, Longhao Zhu, Zhendong Zhang, Neha Senthil, Ruixin Sun
[PDF]
Exploring Contributing Factors to Unemployment
by Sen Zhu Jiachen Pan Xinchang Xiong Dingqi Zhang, Yuewei Wang
[PDF]
MBA Admission Insights and Predictions: Analyzing and Modeling Admission Outcomes
by Shiling Zheng, Zhehan Wang, Xinyu Qian, Xiaozhu Yu, Zairan Xiang
[PDF]
Education and Economic Growth: A Comparative Analysis Using World Development Indicators
by Simen Guttormsen, Jack Stanley, Jay Zhang, Martin Qin, Ziheng Song
[PDF]
Comparing Machine Learning Approaches for Predicting Economic Recessions: A Case Study of Logisitic Regression and Random Forest
by Swiler Boyd, Henry Hai
[PDF]
