Building on Duke’s world-leading stats heritage, the MS in Statistical Science immerses students in probabilistic modeling, causal discovery, and ethics-first data engineering. Cohort teams build federated meta-learning models for hospital consortia, audit large-language-model bias, and lead Data4Good hackathons connecting undergrads, NGOs, and civic leaders.
Hierarchical model forecasting dengue with climate covariates
Causal-impact of minimum-wage hikes on retail employment
Tensor decomposition of fMRI time-series for depression biomarkers
Deep-ensemble uncertainty quantification in autonomous-vehicle vision
Synthetic-control dashboard for city bike-lane rollouts
Differential-privacy library for municipal open-data portals
Spatial point-process study of urban gun-violence hotspots
AutoML pipeline selecting green-chemistry reaction routes
Meta-analysis app summarizing vaccine-trial efficacy
Reinforcement-learning algorithm balancing grid-battery dispatch
Graph neural network identifying poaching hotspots
Explainable boosting machine detecting credit-card fraud
Citizen-science drone image classifier improving flood response
Open-source GitHub action auto-checking project reproducibility
Policy brief on statistical standards for AI auditing
Turn uncertainty into insight with Duke’s powerhouse Stats master’s.
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