Department of Statistical Science

The Department of Statistics, which is located in the University’s Fox School of Business and Management, has 15 full-time graduate faculty members and about forty graduate students in its Master’s and Ph.D. programs.

Research Themes

High-Dimensional Statistics

The study of high-dimensional statistics has emerged in recent years as a brand new field due to the confluence of recent advances in statistics and the ready availability of fast, efficient, and cheap computing. The field of statistics has responded to the urgent need for the development of newer and more appropriate statistical tools to analyze high-dimensional problems involving “Big Data.” It encompasses several emerging fields in statistics, such as high-dimensional statistical inference, dimensionality reduction, data mining, machine learning, and bioinformatics. In fact, many of these and other emerging statistical topics are modernized versions of traditional statistical areas such as multivariate analysis, Bayesian analysis, time series analysis, biostatistics, and statistical computing and graphics.

Biostatistics and Bioinformatics

The Statistics department plans to continue advancing its knowledge and reputation in theoretical, computational, and applied research. Today, the quality and relevance of statistical research is primarily determined by modern applications involving high-dimensional data. Our department enjoys excellence in research in biostatistics, which is closely related to bioinformatics. Preserving that reputation is one of our main research goals. Moreover, one of the objectives of the newly-created Center for High-Dimensional Statistics is to foster and engage in cross-disciplinary research collaborations in the domain of Big Data. This includes interdisciplinary and collaborative research work within the Fox School involving other academic departments and research centers, working with the Biostatistics and Bioinformatics group at the Fox Chase Cancer Center, and collaborating with Temple University’s Center for Data Analytics and Biomedical Informatics located within the College of Science and Technology.

Bayesian Methods

Bayesian methods have become even more important today because of new computational breakthroughs. Members of the Statistics department are developing and applying Bayesian Methods for the statistical analyses of high-dimensional data that arise from research in disciplines such as business, computer science, biology, and medicine.