About PhD

Last update: 11/10/23

PhD Degree in Statistics

The Department of Statistics offers an exciting and recently revamped PhD program that involves students in cutting-edge interdisciplinary research in a wide variety of fields. Statistics has become a core component of research in the biological, physical, and social sciences, as well as in traditional computer science domains such as artificial intelligence and machine learning. The massive increase in the data acquired, through scientific measurement on one hand and through web-based collection on the other, makes the development of statistical analysis and prediction methodologies more relevant than ever.

Our graduate program prepares students to address these issues through rigorous training in scientific computation, and in the theory, methodology, and applications of statistics. The course work includes four core sequences:

  • Probability (STAT 30400, 38100, 38300)
  • Mathematical statistics (STAT 30400, 30100, 30210)
  • Applied statistics (STAT 34300, 34700, 34800)
  • Computational mathematics and machine learning (STAT 30900, 31015/31020, 37710).

All students must take the Applied Statistics and Theoretical Statistics sequence. In addition it is highly recommended that students take a third core sequence based on their interests and in consultation with the Department Graduate Advisor (DGA). At the start of their second year, the students take two preliminary examinations. All students must take the Applied Statistics Prelim. For the second the students can choose to take either the Theoretical Statistics or the Probability prelim. Students planning to take the Probability prelim should take the Probability sequence as their third sequence.

Incoming first-year students have the option of taking any or all of these exams; if an incoming student passes one or more of these, then he/she will be excused from the requirement of taking the first-year courses in that subject. During the second and subsequent years, students can take more advanced courses, and perform research, with world-class faculty in a wide variety of research areas.

In recent years, a large majority of our students complete the PhD within four or five years of entering the program. Students who have significant graduate training before entering the program can (and do) obtain their doctor's degree in three years.

Most students receiving a doctorate proceed to faculty or postdoctoral appointments in research universities. A substantial number take positions in government or industry, such as in research groups in the government labs, in communications, in commercial pharmaceutical companies, and in banking/financial institutions. The department has an excellent track record in placing new PhDs.

Prerequisites for the Program

A student applying to the PhD program normally should have taken courses in advanced calculus, linear algebra, probability, and statistics. Additional courses in mathematics, especially a course in real analysis, will be helpful. Some facility with computer programming is expected. Students without background in all of these areas, however, should not be discouraged from applying, especially if they have a substantial background, through study or experience, in some area of science or other discipline involving quantitative reasoning and empirical investigation. Statistics is an empirical and interdisciplinary field, and a strong background in some area of potential application of statistics is a considerable asset. Indeed, a student's background in mathematics and in science or another quantitative discipline is more important than his or her background in statistics.

To obtain more information about applying, see the Guide For Applicants.

Students with questions may contact Yali Amit for PhD Studies, Mei Wang for Masters Studies, and Keisha Prowoznik for all other questions, Bahareh Lampert (Dean of Students in the Physical Sciences Division), or Amanda Young (Associate Director, Graduate Student Affairs) in UChicagoGRAD.

Handbook for PhD Students