Master of Science
Since the Department's founding in 1984, we have had a consistent vision of the discipline of Statistics and of our role in shaping it through our activities in education, in methodological and applied research, and in support of subject area research, a vision that is consistent with the newly emerged field of Data Science. Throughout its history, the Department has emphasized that the discipline of Statistics derives its importance from applications, but also requires a strong theoretical foundation. The Department has always valued data driven research, consulting, and collaboration, and has long held communication and computing skills as crucial for success. These values are apparent not only in individual faculty members’ research programs but also in our undergraduate and graduate curriculums, and through our consulting and research unit, the Applied Statistics and Data Science Group.
|Chen, Jiahua||finite mixture model, empirical likelihood, asymptotic theory, sample survey|
|Cohen Freue, Gabriela||[field_researcher_interest]|
|Gustafson, Paul||Meta-Analysis, Parametric and Non-Parametric Inference, Theoretical Statistics, Pharmacoepidemiology, Bayesian statistical methods, Causal inference, Evidence synthesis, Biostatistics and Epidemiology, Partial Identification|
|Heckman, Nancy||Statistics and Probabilities, functional data analysis, smoothing, splines|
|Joe, Harry Sue Wah||Statistics and Probabilities, dependence modelling, copula construction, non-normal time series, extreme value inference, parsimonous high-dimensional dependence|
|Nolde, Natalia||Statistics and Probabilities, Multivariate extreme value theory, Risk assessment, Applications in finance, insurance, geosciences|