The B.S. in Statistics and Data Science at UPenn enables students to explore data-driven decision making through statistical theory, programming, and practical application. These project ideas span data visualization, inference, and prediction modeling.
Bayesian Inference in Medical Diagnosis Prediction Models
Modeling Voter Turnout Using Logistic Regression
Data Visualization Dashboard for COVID-19 Global Spread
Sentiment Classification Using Naive Bayes and SVM
Time Series Forecasting for Financial Market Trends
Multivariate Analysis of Air Pollution and Health Metrics
Text Clustering Using TF-IDF and K-Means
Bias and Variance Trade-off in Ensemble Learning Models
Statistical Analysis of NBA Player Performance Trends
Customer Churn Modeling Using Decision Trees
Survival Analysis for Cancer Treatment Outcomes
Data Ethics and Fairness in Predictive Algorithms
Exploratory Data Analysis on Housing Market Trends
Monte Carlo Simulation for Investment Risk
A/B Testing Strategies in E-Commerce Platforms
Collexa mentors UPenn students on statistical modeling, R/Python data analysis, visualization techniques, and reproducible research best practices.
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