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Programs, Requirements, Courses

 

    Program and Requirements for the Ph.D.

    Interdisciplinary Theses

    Consulting and Computation

    Facilities

    Teaching

    Statistics and Computational Mathematics throughout the University

    Programs and Requirements for the M.S.

    Courses

 

Programs and Requirements for the Ph.D.

 

A student applying to the Ph.D. 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 who have not taken courses 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, therefore 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 in determining the ability of the student to do statistical research.

Given the diverse backgrounds of the students, the program is flexible in the timing and content of coursework and research. The following describes a typical path for a student with a solid background in mathematics and some familiarity with statistics. During the first year, the student takes three of the following sequences: probability (STAT 30400, 38100, 38300), mathematical statistics (STAT 30400, 30100, 30200), applied statistics (STAT 34300, 34500, 34700), and computational mathematics and machine learning (STAT 30900, 31000, 37700). At the start of the second year, the student takes preliminary examinations covering two of these areas, one theoretical (probability or mathematical statistics) and one applied (applied statistics or computational mathematics). The choice of sequences and prelims will be done in coordination with the Director of Graduate Studies. During the second year, students take more advanced and specialized courses, depending on their interests. The selection of courses offered varies from year to year, but there is always a variety of courses in probability, in theoretical and applied statistics, in machine learning and in computational mathematics. By the end of the second year, most students should have begun to work with a thesis advisor, usually after taking a reading course with one—or more—prospective advisors. After making substantial research progress, and no later than the end of autumn quarter of the fourth year, the student will identify a thesis committee consisting of an advisor and two other faculty members and will prepare a thesis proposal that is presented to the committee and must be approved. A completed dissertation is presented in a formal departmental seminar, and then a final oral examination completes the program for the Ph.D. In recent years, a large majority of our students complete the Ph.D. 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.

Some students must postpone taking one of the usual first-year sequences in order to first strengthen their background in that area. Such students may (with the approval of the Director of Graduate Studies) defer one of the preliminary examinations to the beginning of the third year. This delay does not usually slow the student's progress through the remainder of the program.

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.

 

Interdisciplinary Theses

 

Many of our students choose to pursue research combining statistics and computation with another area of scientific research, such as genetics, neuroscience, health studies, environmental science, economics, and others. Students who choose to write an interdisciplinary thesis can work with a thesis advisor from another department as long as the two other committee members are from the Statistics Department.

 

Consulting and Computation

 

Students in the degree programs are encouraged to complement their training in statistics with experience and study in some field where statistics is important. Courses and study in empirical science and summer employment offer opportunities in this direction. The department operates a consulting program under the guidance of the faculty, of service mainly to students and faculty throughout the University. All degree candidates in Statistics are expected to participate in the consulting program, usually by working in one or more teams devoted to particular consulting projects. An informal seminar meets regularly to provide a forum for presenting and discussing problems, solutions, and topics in statistical consultation. Students present interesting or difficult consulting problems to the seminar as a way of stimulating wider consideration of the problem and developing familiarity with the kinds of problems and lines of attack that are involved. Often the consultee will participate in the presentation and discussion.

 

Facilities

 

Almost all departmental activities and facilities—classes, seminars, computing equipment, and student and faculty officesare located in Eckhart Hall or neighboring Ryerson Hall. Each student is assigned a desk in one of several offices. A small departmental library and conference room is used as a common meeting place for formal and informal gatherings of students and faculty. The major computing facilities of the department are based upon a network of PCs running mainly Linux. There are a few computers in each student office. There is also a computer lab, which we share with the Math Department.

 

Teaching

 

Part of every statistician's job is to evaluate the work of others and to communicate knowledge, experience, and insights. Every statistician is, to some extent, an educator, and we provide our graduate students with training and experience for this aspect of their professional lives. We expect all doctoral students, regardless of their professional objectives and sources of financial support, to participate in undergraduate and graduate instruction, first as teaching assistants and, later, as lecturers with responsibility for an entire course.

 

Statistics and Computational Mathematics throughout the University

 

In addition to the courses, seminars, and programs in the Department of Statistics, courses and workshops with strong connections to statistics and computational mathematics  occur throughout the University, most notably in  Human Genetics, Computational Neuroscience, Health Studies, Economics, the Computation in Science Seminar, Computer Science, the Toyota Technical Institute, the Statistics and Econometrics program at the Booth School, the Financial Mathematics program, and NORC (formerly the National Opinion Research Center).

 

Programs and Requirements for the M.S.

 

The background needed for M.S. students is essentially the same as for Ph.D. students except that courses in mathematics beyond advanced calculus and linear algebra are less crucial. The main requirements of the M.S. program are a sequence of nine approved courses plus a Master's paper. The nine required courses must include a three-quarter sequence in applied statistics (STAT 34300, 34500, 34700) and a three-quarter sequence in statistical theory and methods (STAT 24400, 24500, 24610). The other three courses are chosen in consultation with the student's advisor. The master's paper does not require original research. A common topic for a paper is a thorough analysis of some real data set. In addition to the coursework and paper, M.S. students are also expected to participate in the departmental consulting program. For a student with the appropriate background, the M.S. program can be readily completed in one calendar year.

 

Courses

 

See http://graduateannouncements.uchicago.edu/graduate/departmentofstatistics/#courseinventory for a listing of all courses offered by our department.