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Program Course Requirements & Timetables

Statistics Lecture

Each student in the program arrives with a different level of preparation, and not all students will necessarily be required to take all courses as specified below. In particular, with approval of the Director of Graduate Studies, coursework taken elsewhere may be used to satisfy certain requirements.

PhD: Courses and Study Timetable

STSCI 7170 Linear Models (Fall, Year 1)
MATH 6710 Probability (Fall, Year 1)
STSCI 7180 Generalized Linear Models (Spring, Year 1 or 2)
STSCI 6520 Statistical Computing (Spring, Year 1 or 2)
MATH 6720 Probability II or STSCI 6750 Probability II for Statisticians (Spring, Year 1)
STSCI 6730 Theory of Statistics (Spring, Year 1)
MATH 6740 Asymptotic Statistics (Fall, Year 2)
BTRY 7950 Statistical Consulting (Fall, Year 2 or 3)
BTRY 7951 Advanced Statistical Consulting (Spring, Year 2 or 3)

At the end of the first year, a First Year Evaluation is conducted; depending on the outcome, a student may have to take a written qualifying examination. In addition, students are required to take 4 - 5 elective courses that will need to be approved by their Special Committee Chairperson.

A and B Exams

The Statistics PhD program has two primary exam requirements, the Admission to Candidacy Exam (A-Exam) and the Oral Defense of Dissertation (B-Exam). The Graduate School requires all PhD students to have their A-Exam prior to the beginning of their 7th semester in the program. Doctoral degree candidates will take their B-Exam upon completion of all degree requirements, but students must also pass their A-Exam at least two semesters prior to their B-exam. The Field of Statistics expects PhD students to schedule and pass their B examination within 5 years of entering the PhD program.

Student Progress Review/Annual Progress

The Graduate School requires that all PhD students in their second year and beyond complete a yearly Student Progress Review (SPR). The SPR is designed to foster constructive communication between students and faculty regarding academic and research progress. 

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