The BA in Applied Statistics at the University of Virginia empowers students to explore real-world phenomena using data-driven methods. Emphasizing both theoretical rigor and practical application, the program covers statistical modeling, probability, computational tools, and data visualization. Students engage with statistical software, interpret results, and design experiments for various domains such as economics, healthcare, policy, and sports analytics. The curriculum supports interdisciplinary learning and includes opportunities for research, internships, and capstone projects. Graduates are well-positioned for careers in analytics, consulting, or further graduate study in quantitative fields. Applied Statistics at UVA is ideal for those who love problem-solving and quantitative reasoning.
Predicting NCAA basketball outcomes using logistic regression
Sentiment analysis on social media platforms during election cycles
Bayesian modeling of medical treatment efficacy
Linear regression analysis of housing price trends in Virginia
Random forest modeling for customer churn prediction
Designing and analyzing A/B testing in digital marketing
Data cleaning pipelines for large-scale survey data
Survival analysis in clinical trial datasets
Multivariate analysis of crime data across counties
Spatial statistics for air quality monitoring networks
ANOVA comparison of teaching methods in K–12 education
Monte Carlo simulations of economic forecasting scenarios
Time series analysis of energy consumption data
Building predictive models for loan default risk
Logistic regression on student performance outcomes
Machine learning classifier for disease diagnosis
Analysis of polling errors in national elections
Data visualization dashboards for public health trends
Meta-analysis of studies on vaccine effectiveness
Text mining in online consumer reviews for brand sentiment
Master data, models, and statistical thinking in UVA’s Applied Statistics program.
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