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Ph.D. Degree
Description
This is a very brief description of the PhD in Statistics. More details of this program can be found in the graduate catalog.
Students usually enter this program with a MS in Statistics. If they have not done it previously, they must pass the written masters exam at the Ph.D. level. Students are required to take additional course work beyond the masters level. They are required to pass three Preliminary exams. Two of them are over linear models (Stat 6630 & 6610) and inference (Stat 6650 & 6660). The third one is based on two (students' choice) of the following methods courses:
- Time Series
- Survival Analysis
- Robust Analysis
- Categorical Analysis
- Second Course in Design
These elective courses are a blend of theory and methods. Usually the student takes these exams after finishing the particular sequence of courses. Most of the course work as well as the dissertation will involve statistical computing. Our Statistical Computing Lab provides hardware and software for this work.
Ph.D. students select their own advisor from the faculty in the Department of Statistics. This would allow the dissertation topic to be of interest to the student and his/her advisor. Theses can range from theoretical to applied and we encourage cross-disciplinary work.
The program consists of 75 credit hours including 15 hours of dissertation credit. The 60 hours of course work includes work for an MS which is usually about 30 hours. Hence for most students with an MS in Statistics, the course work for a PhD consists of about 30 hours.