Harvard’s Statistics BS delivers a robust foundation in probability theory, inference, and machine learning, complemented by intensive computing in R and Python. Students analyze big-data sets from genomics, sports analytics, and social science while collaborating with the Harvard Data Science Initiative. Graduates advance to roles in tech, healthcare, and policy where data-driven decisions shape the future.
Bayesian model estimating vaccine efficacy over variants
Random-forest classifier for wildlife-camera image data
Interactive Shiny app visualizing income inequality trends
Meta-analysis of clinical-trial survival curves
Hierarchical model of baseball player performance
Study on p-hacking prevalence in psychology journals
Capstone forecasting election outcomes with ensemble methods
Algorithm detecting bias in predictive policing data
Time-series clustering of cryptocurrency markets
Bootstrapping approach to uncertainty in climate projections
R package for visualizing multivariate outliers
Causal-inference study on remote-learning impacts
Deep-learning model predicting protein-fold stability
Consulting project optimizing hospital staffing schedules
Dashboard monitoring air-quality sensors in real time
Workshop on ethical data storytelling techniques
Research on differential privacy in census microdata
Learn to wrangle, model, and communicate data for high-impact decision-making.
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