Statistics and Probability
Graduate study in statistics and probability has taken on a new look and increased importance in the last two decades due to dramatically increased computational power and the aggressive and highly successful application of statistical methods by our competitors in the world marketplace. In particular, the Japanese have extensively employed design of experiments, data analysis and statistical process control to improve the quality of their processes and the quality of their manufactured products.
Recently, a number of major U.S. corporations began emulating the Japanese approach by getting management to support the introduction of “statistical thinking” throughout companies, and requiring that the people running their processes have sufficient formal training in statistics to properly implement and monitor statistical process control programs.
Faculty
Faculty involved with statistics and probability include:
- D. Andrew Brown: Bayesian analysis, neuroimaging data analysis, large-scale inference.
- Colin Gallagher: limit theorems, time series, modeling heavy-tailed data.
- Xinyi Li: Precision medicine, non- and semi-parametric regression, functional data analysis, neuroimaging, spatio-temporal analysis, sparse learning, statistical genetics.
- Christopher McMahan: Categorical data analysis, group testing, survival analysis, Bayesian estimation, statistical computing.
- Xiaoqian Sun: Statistical decision theory, Bayesian Statistics, multivariate analysis, and bioinformatics.
- Calvin L. Williams: Biostatistics, computational statistics, categorical data.
- Qiong Zhang: Experimental design and statistical modeling for computer experiments, uncertainty quantification.
Other Resources
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Curriculum
Find out more about the curriculum and course descriptions for this interest area.
