Master of Science in Statistics
Doctor of Philosophy

For More Information

Campus address: Welch Hall (WEL) 5.216, phone (512) 232-0693, fax (512) 475-8297, campus mail code: D9800

Mailing address: The University of Texas at Austin, Graduate Program in Statistics, Department of Statistics and Data Science, 105 E. 24th St. Stop D9800, Austin TX 78712

E-mail: stat.admin@austin.utexas.edu

URL: https://stat.utexas.edu/academics#graduate-programs

Facilities for Graduate Work

The Department of Statistics and Data Sciences (SDS) is primarily located in Welch Hall, which houses the department’s administrative suites and office space for the tenured/tenure-track faculty. PhD students and postdocs have shared office space in Welch Hall. This newly renovated space also includes three state-of-the-art conference rooms and a flexible collaboration space. In addition, the department maintains a footprint in the Dell Gates Complex (GDC), which is located immediately across the street from Welch Hall. The department’s instructional faculty have offices in GDC and flexible space is used for informal instruction and office hours. The department’s statistical consulting center is located in GDC. The department partners with the Population Research Center and the Texas Advanced Computing Center to provide support for secure data and computationally intensive research.

Areas of Study

Graduate degree candidates are expected to develop broad competence in the discipline of Statistics as a whole as well as expertise in their chosen area of concentration. The Master of Science in Statistics is a two-year program that offers advanced training for students in classical and modern statistical methods. The program is designed for students preparing for careers in statistical professions, as well as those seeking additional statistical training while pursuing a doctoral degree in another discipline. The PhD in Statistics is a five-year degree that focuses on training students in the theory and practice of modern statistical science and computation so that they are prepared to make novel contributions to the field. Major emphasis is placed on training in application-driven methodological research, probability modeling, and statistical computation. Throughout the program, students are exposed to central ideas of both Bayesian and classical approaches to statistical inference, as well as statistical machine learning methodology.

Graduate Studies Committee

The following faculty members served on the Graduate Studies Committee (GSC) in the spring 2023 semester.

The GSC Committee list was not available at publication time; please check directly with the department for an up-to-date list.