PhD in Biostatistics
Overview of the PhD Degree
The PhD program in Biostatistics is geared toward the graduate student who seeks a career as a professional, academic, or industrial biostatistician in biomedical or epidemiologic sciences. The program meets the needs of the health professional who wishes to continue with public health training and achieve a higher and more specialized degree and the statistician who wishes to specialize in statistical methods for biomedical or epidemiologic applications.
PhD Degree Requirements
The School of Public Health (SPH) and the Graduate School of Arts & Sciences (GRS) require students pursuing a Doctor of Philosophy in Biostatistics to:
- Complete the 64-credit curriculum
- Fulfill the Residency Requirement
- Fulfill the Language Requirement
- Fulfill the Grade Requirement
- Pass the Qualifying Examinations
- Participate in one doctoral dissertation presentation per year
- Attend at least one doctoral dissertation presentation per month
- Complete dissertation that is the equivalent of three publishable papers
- Pass Final Oral Defense Examination
- Complete the PhD degree within seven years (post-bachelor’s) or five years (post-master’s)
The intent of the curriculum is to provide a firm foundation in biostatistics and mastery of a broad range of applied techniques.
Students in the PhD program entering with only a bachelor’s degree must complete a total of 64 credits.
Students entering the PhD program with an MA may be accepted into an eight-course post-master’s PhD program. However, they may be required to take extra courses if there are deficiencies in their background. For post-master’s PhD students, the core courses required will be determined at the start of their program by the Co-Directors. The remaining courses must come from the list of Biostatistics (either BS or MA series) or elective courses.
Nine core courses (35 credits):
- CAS MA 575 Linear Models (4 cr)
- CAS MA 581 Probability or MET MA 581 Probability (4 cr)
- CAS MA 582 Mathematical Statistics or MET MA 582 Mathematical Statistics (4 cr)
- SPH EP 713 Introduction to Epidemiology (3 cr)
- SPH BS 805 Intermediate Statistical Computing and Applied Regression Analysis (4 cr)
- SPH BS 852 Statistical Methods for Epidemiology (4 cr)
- SPH BS 853 Generalized Linear Models with Applications (4 cr)
- GRS MA 781 Estimation Theory (4 cr)
- GRS MA 782 Hypothesis Testing (4 cr)
At least four of the following electives, including at least one each from the MA and BS Series (16 credits):
- CAS MA 576 Generalized Linear Models (4 cr)
- CAS MA 583 Introduction to Stochastic Processes (4 cr)
- CAS MA 584 Multivariate Statistical Analysis (4 cr)
- CAS MA 585 Time Series Modeling and Forecasting (4 cr)
- CAS MA 586 The Design of Experiments (4 cr)
- CAS MA 587 Sampling Design: Theory and Methods (4 cr)
- CAS MA 588 Nonparametric Statistics (4 cr)
- CAS MA 685 Advanced Topics in Statistics (4 cr)
- GRS MA 750 Advanced Statistical Methods I (4 cr)
- GRS MA 751 Advanced Statistical Methods II (4 cr)
- SPH BS 722 Design and Conduct of Clinical Trials (4 cr)
- SPH BS 728 Public Health Surveillance—a Methods Based Approach (2 cr)
- SPH BS 775 Applications of Statistical Methods in Clinical Research (4 cr)
- SPH BS 810 Meta-analysis for Public Health and Medical Research (4 cr)
- SPH BS 820 Logistic Regression/Survival Analysis (4 cr)
- SPH BS 821 Categorical Data Analysis (4 cr)
- SPH BS 822 Advanced Statistical Computing (4 cr)
- SPH BS 830 Design and Analysis of Microarray Experiments (4 cr)
- SPH BS 845 Applied Statistical Modeling and Programming in R (4 cr)
- SPH BS 850 Computational Biology (4 cr)
- SPH BS 851 Applied Statistics in Clinical Trials I (4 cr)
- SPH BS 854 Bayesian Methods in Clinical Trials (4 cr)
- SPH BS 855 Bayesian Modeling for Biomedical Research (4 cr)
- SPH BS 857 Analysis of Correlated Data (4 cr)
- SPH BS 858 Statistical Genetics I (4 cr)
- SPH BS 859 Applied Genetic Analysis (4 cr)
- SPH BS 860 Statistical Genetics II (4 cr)
- SPH BS 861 Applied Statistics in Clinical Trials II (4 cr)
The remaining credits may be selected from the above series of courses or from the following electives. One elective may be in the biological sciences (13 credits):
- CAS MA 511 Introduction to Analysis I (4 cr)
- CAS MA 512 Introduction to Analysis II (4 cr)
- CAS MA 539 Methods of Scientific Computing (4 cr)
- CAS MA 555 Numerical Analysis I (4 cr)
- CAS MA 556 Numerical Analysis II (4 cr)
- CAS MA 578 Bayesian Statistics (4 cr)
- GRS MA 703 Statistical Analysis of Network Data
- GRS MA 711 Real Analysis (4 cr)
- GRS MA 750 Advanced Statistical Methods I (4 cr)
- GRS MA 751 Advanced Statistical Methods II (4 cr)
- GRS MA 779 Probability Theory I (4 cr)
- GRS MA 780 Probability Theory II (4 cr)
- GRS MA 861* Seminar: Applied Mathematics (4 cr)
- GRS MA 882* Seminar: Statistics (4 cr)
- SPH BS 771 Topics in Biostatistics (also 871) (4 cr)
- SPH EP 813 Intermediate Epidemiology (4 cr)
- SPH EP 854† Modern Epidemiology (4 cr)
- SPH EP 855† Design Issues in Epidemiology (4 cr)
- SPH EP 856† Selected Topics in Epidemiologic Methods (4 cr)
- SPH BS 901** Directed Study in Biostatistics (variable credit)
- SPH BS 902** Directed Research in Biostatistics (variable credit)
* Only one of these courses may count as an elective.
† Only one of these three courses may count as an elective.
** Post-bachelor’s PhD students may petition Co-Directors to allow more than 4 credits.
# Given the large number of biology courses, a comprehensive list is not provided here. Please contact the Program Directors to seek permission for a specific course in the biological sciences.
The minimum residency requirement is the equivalent of two consecutive regular semesters of full-time graduate study at Boston University. Students who have completed their course requirements must register each subsequent academic-year semester for BS 980 Continuing Study/Dissertation Seminar until they have completed all requirements for the degree. Upon written petition and appropriate cause, students will be allowed up to two semesters of leave of absence. Students must be registered in both the semester in which the last degree requirements are completed and in the preceding semester. For further information on residency requirements, see the Policies section of this website.
Students must demonstrate proficiency in reading the biostatistical literature in a language other than English. International students whose native language is not English may use English to fulfill the language requirement. Students who have not previously completed at least two years of study in a foreign language at the undergraduate level or the equivalent must make up the deficiency through coursework or examination.
Students must earn a minimum grade of B− in all courses applied to the PhD.
The doctoral candidate must satisfactorily pass two comprehensive written examinations upon completion of coursework. These will require proficiency in the material covered in the nine core courses. Students are allowed two attempts to pass a qualifying exam. The Biostatistics Qualifying Exam Committee will evaluate requests by students to take an exam for the third time on a case-by-case basis.
Upon successful completion of the qualifying examinations, doctoral students select thesis advisors who guide them through their dissertation research. The PhD dissertation provides the student with the opportunity to design, conduct, and report on independent, original research in biostatistics. The dissertation consists of original research in the development of statistical methodology for biomedical or epidemiologic applications. The dissertation must be an original contribution to the body of knowledge in biostatistics. It is expected that the dissertation content will address a relevant question in statistical methodology and pose a new approach, extend an existing approach, or provide novel application of an existing method. Dissertations will often utilize simulation, but simulation studies without methodological development or a theoretical component are not sufficient. Additionally, simulations are not required and use of real data sets in combination with theoretical work may suffice.
The dissertation must meet all formatting requirements specified by the Graduate School of Arts & Sciences. Within these requirements, two approaches to the dissertation are allowed. The first is a single body of work comprehensively addressing one problem. The second format consists of two or three problems in a single area of research. For either format, the content of the dissertation should be at least equal to the content of three journal articles. The format of the dissertation (single body of work versus multiple related problems) should be a consensus among the student, the major advisor, and the committee members.
Doctoral Dissertation Presentations
Bi-monthly seminars are held throughout the academic year for student presentations. Students who have completed coursework and have passed their qualifying examinations must (a) present the status of their thesis work in at least one seminar per year, and (b) attend at least one seminar each month. There are no exceptions.
In addition, students are required to complete a paper based on their dissertation that is ready to submit to a peer-reviewed journal for consideration of publication, and be listed as first author. The article must conform to the requirements of a specific statistical or otherwise appropriate journal.
Final Oral Exam
The candidate presents an oral defense of the dissertation before a five-member doctoral committee. The schedule for planning the Final Oral Examination is available at the GRS Graduate Information website.
The post-bachelor’s PhD program must be completed within seven years after the first registration for doctoral study. The post-master’s PhD program must be completed within five years after the first registration for the doctoral program.
Diploma applications and calendar are available in the Graduate School of Arts & Sciences (GRS) Records Office, 705 Commonwealth Avenue, Suite 112, or online at the GRS Graduate Information website.