Statistics: operations research for health care, spatial statistics, spatial envirometrics, forest fire modeling, mark recapture models, history of statistics, survey sampling, statistical software, statistical computing, time series analysis, stochastic processes, inference, lifetime data analysis, biostatistics.
Statistics is the science and art of the interpretation and understanding of data in a rigorous way through mathematical models and probability theory, the science of chance. Modern data analytic methods rely heavily on computing.
If you are interested in graduate work in this research area, direct your application to the Department of Statistical and Actuarial Sciences.
- David Bellhouse - History of probability, statistics, and actuarial science, survey sampling design and analysis.
- Simon Bonner - Mark recapture methods, wildlife ecology modeling. (Joint with Biology.)
- John Braun - Inference, statistical computing, smoothing techniques, forest fires.
- Charmaine Dean - Longitudinal and life-history analysis, forests, fires, and stochastic models, mapping disease and mortality rates.
- Jörn Diedrichsen - Spatio-temporal models of neural activity, brain imaging analysis
- Wenqing He - Lifetime data analysis, longitudinal data analysis, data mining, biostatistics.
- Reg Kulperger - Inference, bootstrapping, smoothing techniques, asymptotic methods, applied stochastic modelling, mathematical finance.
- Ian McLeod - Time series analysis, data mining, bayesian analysis, statistical software development.
- Serge Provost - Multivariate analysis, quadratic forms, inference with incomplete data.
- Hristo Sendov - Optimization, variational analysis, financial mathematics.
- David Stanford - Operations research for health care and forest fires, queueing theory, ruin theory.
- Douglas Woolford - Data science/analytics to study wildland fire science and wildland fire management; risk assessment and modelling; stochastic and statistical modelling using large and complex spatio-temporal data structures in environmetrics.
- Hao Yu - Statistical computing, parallel programming, financial time series, stochastic modelling, approximation in statistics and probability.
- Ricardas Zitikis - Stochastic modelling in economics, actuarial science, time series analysis, stochastic processes.