Yale’s Statistics and Data Science program emphasizes data literacy, statistical reasoning, machine learning, and ethical data use. These projects help students turn data into decisions using rigorous quantitative methods.
Predicting Student Academic Success Using Regression Models
Sentiment Analysis of Social Media Data Using NLP
Bayesian Inference in Clinical Trial Outcome Prediction
Time Series Forecasting for Stock Market Indices
Data Visualization Dashboard for Public Health Trends
Fraud Detection in Online Transactions Using Decision Trees
Churn Prediction Model for Subscription-Based Platforms
Clustering Customer Segments in E-commerce Data
Evaluation of Sports Performance Using Statistical Metrics
Exploratory Data Analysis of Global Climate Change Indicators
Building a Recommendation Engine with Collaborative Filtering
A/B Testing Framework for Website Design Optimization
Analysis of Crime Data Using Geospatial Statistics
Survival Analysis of Patient Data in Cancer Studies
Big Data Pipeline for Real-Time Transportation Insights
Collexa supports Yale students with data pipeline design, predictive modeling, visualization tools, and end-to-end project documentation.
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