Professor Daniel Heitjan, Department Chair
Professors: Ronald Butler, Jing Cao (Director of Graduate Studies), Daniel Heitjan (Director of the Biostatistics Ph.D. Program)
Associate Professors: Ian Harris, Monnie McGee
Assistant Professors: Sy Han (Steven) Chiou, Marcin Jurek, Chul Moon, Raanju Sundararajan
Technical Assistant Professor: Bivin Sadler
Assistant Professor of Practice: Charles South
Senior Lecturer: Stephen Robertson
Lecturers: Ashley Edison, Jessica Wickersham
The Department of Statistics and Data Science offers the following graduate degree programs: the Ph.D. in statistical science, the Ph.D. in biostatistics, the Ph.D. in data science, the M.S. in applied statistics and data analytics, and the M.S. in data science.
The courses in the biostatistics and statistics Ph.D. curricula provide students with a strong foundation in mathematical statistics, statistical computing, and probability, and statistical methods useful in statistical practice. The Ph.D. in biostatistics is conferred by the Department of Statistics and Data Science at SMU in partnership with the University of Texas Southwestern Medical Center at Dallas. Students attain a strong mathematical and statistical foundation such as that provided in the Ph.D. in statistical science curriculum, but they also take courses and engage in research projects that prepare them for a research career in biostatistics. The Ph.D. in data science draws its core material from the doctoral curricula in statistics and computer science. Students apply this knowledge in the solution of challenging applied problems from a range of disciplines.
The M.S. in applied statistics and data analytics (MASDA) degree program provides students with a theoretically-based understanding and proficiency in statistical methods, as well as training in statistical computing, database management, predictive methods, and other data science techniques.
The M.S. in data science (MSDS) is an online degree program that provides students with a theoretically-based understanding and proficiency in the management, analysis, mining, and interpretation of complex databases to support strategic decision-making.
Note: In all three doctoral programs, a student advances to candidacy after passing comprehensive and qualifying exams, preparing a written prospectus, and giving an oral presentation in a research area on which the dissertation will be based.