The MS in Statistics at the University of Florida equips students with deep theoretical knowledge and practical tools in statistical inference, regression analysis, Bayesian methods, and multivariate modeling. With training in R, Python, and SAS, graduates are prepared to contribute to data-driven solutions in research, healthcare, tech, and finance, or to pursue doctoral study.
Thesis on Bayesian survival analysis in cancer clinical trials
Development of predictive models for academic retention using logistic regression
Application of multivariate analysis in environmental pollution studies
Modeling customer churn with machine learning and classification trees
Simulation study on small sample performance of bootstrap confidence intervals
Design and evaluation of experiments in agricultural yield optimization
Thesis on missing data imputation in large-scale social science surveys
Factor analysis of psychological assessment tools in adolescent mental health
Hierarchical modeling of sports performance across multiple seasons
Meta-analysis of vaccine effectiveness across diverse population subgroups
Development of a statistical control chart for hospital infection rates
Design and implementation of randomized block designs in educational studies
Study of variance components in multi-site clinical trials
Principal component analysis for high-dimensional genomic data
Cross-validation framework for tuning predictive health risk models
Longitudinal modeling of weight loss trajectories in intervention programs
Analysis of housing price determinants using multiple regression models
Time-series forecasting of retail sales using ARIMA and exponential smoothing
Thesis on proportional hazards assumptions in Cox regression models
Survey design and sampling strategy evaluation in public opinion polling
Master the tools of statistical reasoning to solve complex problems in science and industry.
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