Graduate Studies in Statistics at Rice
Graduate students in Statistics at Rice have the opportunity for rigorous training in theoretical statistics as well as applied research in a wide spectrum of topics in applied, theoretical and computational statistics from engineering, natural sciences, business, medicine, and social sciences. Students may work towards one of the three graduate degrees offered: master's without thesis (M.Stat.), master's with thesis (M.A.), or doctoral degree (Ph.D.). The M.A. degree is offered only in conjunction with the Ph.D. ¬†
The discipline of statistics is applied broadly, enabling advances in areas where extracting information from massive data sets is crucial. At Rice, this translates to multidisciplinary efforts that cut across departments and institutions. We have collaborative programs in these areas:
These programs, with the exception of Computational Finance, are exclusively for students in the Ph.D. program. The Center for Computational Finance also has an undergraduate minor and a program for professional master's students.
The department, the George R. Brown School of Engineering, and the university computing center offer a wide range of computing equipment. Computing is an integral part of education and research in the department, and the faculty are committed to maintaining a first-class computing environment for students. The department maintains a network of servers for its core computing and each full-time graduate student is provided with a desktop computer. ¬†
Rice Statistics Ph.D. graduates have excelled in faculty positions at other leading universities, in industry, and in government laboratories and agencies. Rice's small size works to its advantage: graduate students work closely with the faculty in small research groups that often cross departmental and disciplinary boundaries, and even institutional boundaries. Examples of our department‚Äôs commitment to interdisciplinary efforts are the subspecialties within our program in biostatistics, bioinformatics, statistical genetics and computational finance. We also engage in collaborative research beyond these specialties, such as neuroscience, energy and environmental statistics, reliability of systems and cities, and statistical process control. Our faculty undertakes challenging interdisciplinary problems for which our expertise in developing new statistical methodologies can make a difference. Students have the opportunity to interact with faculty from other departments, including our sister computational engineering departments of computer science, computational and applied mathematics, and electrical and computer engineering.
For more information about our programs, send email to: firstname.lastname@example.org
or write to:
Chair, Graduate Committee
Department of Statistics, MS 138
PO Box 1892
Houston, TX 77251