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Programs

Statistics

The Department of Biostatistics and Computational Biology offers programs leading to the master of arts (MA) and doctor of philosophy (PhD) in statistics. The non-thesis MA program can be completed in three semesters or, in some cases, one calendar year. The PhD program generally requires a minimum of four years of study, with five years being more common. PhD students may pursue a traditional program of study or the concentration in bioinformatics and computational biology.

The program interprets “statistics” very broadly, with specialization available in probability, statistical theory and analysis, biostatistics, and interdisciplinary areas of application. The curriculum is designed to give students a thorough grounding in statistical theory, which provides the necessary foundation for successful research in statistical methodology. The curriculum also gives students an appreciation for applied problems in biomedical research and the skills necessary to succeed in collaborative research environments. An important goal is to produce graduates with a command of technical skills and the ability and experience to use them appropriately.

Faculty participate fully in graduate teaching and give individual attention to each student through intensive advising. Program faculty have research interests and expertise in virtually all areas of modern theoretical and applied statistics. Faculty are involved in wide-ranging collaborative activity with basic science and clinical departments in the School of Medicine and Dentistry. This environment is ideally suited for training in research in statistical methodology, collaborative research, and consulting.

Information about faculty and research can be found on the Statistics website.

AdmissionsLink to section

Applying to Master's ProgramsLink to section

The requirements for application, admission, and entry into the terminal MA program are the same as those for the PhD unless otherwise indicated. Doctoral students are automatically and initially considered MA candidates.

Entering MA students should have a strong background in mathematics, including three semesters of calculus (through multivariable calculus), a course in linear and/or matrix algebra, and a year of probability and mathematical statistics. A course in real analysis is encouraged; a course in statistical methods is also recommended.

A request for part-time study in the MA program should be identified in the online application and will be subject to the MA program director’s approval. Applicants interested in part-time study are encouraged to contact the department before submitting the application.

Applicants will interview with at least two program faculty members before an admissions offer is recommended. Students entering with advanced training in statistics may transfer credits at the discretion of the MA program director and in accordance with University policy.

Current and eligible University of Rochester undergraduate students have the opportunity to pursue the MA degree through an accelerated option (4+1). Applications should be submitted before the end of the junior year to the Department of Biostatistics and Computational Biology. Accepted students may complete up to three graduate-level BST courses during their senior year that count towards both their Bachelor's degree and the MA in statistics degree. Students are assigned a biostatistics faculty advisor, in addition to their undergraduate academic advisor.

Applying to Doctoral ProgramsLink to section

A candidate for admission to the PhD program should have a strong background in mathematics, including three semesters of calculus (through multivariable calculus), a course in linear and/or matrix algebra, and a year of probability and mathematical statistics. A course in real analysis is encouraged; a course in statistical methods is also recommended. While some background in biology may be helpful for pursuing certain avenues of research, it is not required for admission to the traditional statistics program. Basic courses in computer science and/or biology are recommended for students pursuing the concentration in bioinformatics and computational biology.

Applicants must have earned a U.S. baccalaureate degree or its equivalent from a college, university, or technical school of acceptable standing. Students in their final year of undergraduate study may be admitted on the condition that their bachelor’s degrees are awarded before they matriculate. Evidence of the earned degree is required before matriculation in the form of an official transcript noting degree conferral.

Applicants must submit the following materials for consideration in their online application: statement of purpose, transcripts from all previous college and graduate programs, and three letters of recommendation. Most international applicants will also need to provide evidence of English proficiency (e.g., TOEFL, IELTS, or DuoLingo test score unless approved for a waiver). Applicants may choose to submit additional materials, such as a CV/resume and research papers.

Applicants will interview with at least three program faculty members before an admissions offer is recommended. Students are admitted to the PhD program as a whole, rather than to work directly with individual professors. Full-time study is required.

Students entering with advanced training in statistics, bioinformatics, or computational biology may transfer credits at the discretion of the PhD program director and in accordance with University policy.

AcademicsLink to section

Master's Degrees and RequirementsLink to section

The Master of Arts in Statistics prepares students for both master’s-level statistician work and doctoral programs. The MA degree requires satisfactory completion of at least 32 credits and a final comprehensive written examination. There are no thesis or language requirements. A balanced program is worked out with the MA program director. The typical program of study includes eight courses.

A typical full-time program for the MA consists of PhD-level courses taken in semesters one (three courses), two (three courses), and three (two courses); however, MA students have the option of completing the program in two semesters (four courses per semester). The final comprehensive examination is administered during the summer after the first year of study.

Students in the PhD program receive the MA degree upon satisfactory completion of the requirements for the degree.

Doctoral Degrees and RequirementsLink to section

PhD Statistics (traditional program)

A program of study will be determined individually with the PhD program director. Students are required to take a minimum of 16 formal courses. Additional courses can be taken for audit or credit. PhD students are required to register for at least four semesters of Seminar in Statistical Literature, a one-credit course offering extensive practice in searching the statistical literature and preparing and delivering presentations. All PhD students are required to earn at least four credits of supervised teaching and/or supervised consulting and one credit of Ethics and Professional Integrity in Research. There is no foreign language requirement. Programming expertise is developed in the program.

Course work in statistics is concentrated in three areas: probability, inference, and data analysis. Beginning students should expect to spend all of their first year, most of their second year, and some of their third year taking formal courses. The balance of time is spent on reading and research.

Students take a comprehensive (basic) examination at the beginning of the second year and another written (advanced) exam at the beginning of the third year. Both cover material in the areas of probability, inference, and data analysis. PhD students receive the MA degree after passing the comprehensive (basic) examination and completing 32 credits of coursework.

After beginning research on a dissertation topic, PhD students take an oral qualifying examination, consisting largely of a presentation of a thesis proposal to a faculty committee, the student’s thesis committee. Upon completion of the dissertation, doctoral candidates present their work at a public lecture followed by an oral defense of the dissertation before the thesis committee.

Students must spend 40 months to 66 months, not necessarily continuously, engaged in one or more of the following activities that enhance their education and skills as statisticians: teaching assistantship, research assistantship, participation on the statistical consulting rotation, and summer internships. Students are also expected to be the primary author on a peer-reviewed journal article submitted for publication before defending their PhD research.

PhD Statistics (concentration in bioinformatics and computational biology)

Formal course and examination requirements for students in the bioinformatics and computational biology (BCB) concentration are essentially the same as those for students in the traditional statistics program, with the main differences being in some required and elective courses related to bioinformatics and computational biology.

Students in the BCB concentration are required to take three courses related to bioinformatics and computational biology, while those courses are optional for students in the traditional statistics program. BCB concentration students are also required to answer certain questions related to one of these courses on the advanced examination. A student can switch from the BCB concentration to the traditional statistics program at any time, but students in the traditional statistics program can switch to the BCB concentration only before taking the advanced examination. Basic courses in computer science and/or biology are recommended for those applying to the BCB concentration.

Considerations for Students in the MD/PhD Program

Students admitted to the MD/PhD program follow essentially the same course of study as students in the PhD program, except that coursework in statistics begins during the fall of the third year in the program. During the first year, students spend three months (June to August) with a mentor to begin the process of orientation toward research in statistical methodology. This is repeated during the second year of the program (March to August) just before the start of coursework. The main goals of these interactions are to give the student some insight regarding the process of research in statistical methodology and to facilitate the process of choosing a research advisor.

Graduate Course TitlesLink to section

  • BST 401: Probability Theory
  • BST 402: Stochastic Processes
  • BST 411: Statistical Inference I
  • BST 412: Statistical Inference II
  • BST 413: Bayesian Inference
  • BST 426: Linear Models
  • BST 430: Introduction to Statistical Computing
  • BST 432: High Dimensional Data Analysis
  • BST 433: Computational Systems Biology
  • BST 434: Genomic Data Analysis
  • BST 450: Data Analysis
  • BST 452: Design of Experiments
  • BST 461: Biostatistical Methods I
  • BST 462: Biostatistical Methods II
  • BST 463: Introduction to Biostatistics
  • BST 465: Design of Clinical Trials
  • BST 467: Applied Statistics in the Biomedical Sciences
  • BST 479: Generalized Linear Models
  • BST 487: Seminar in Statistical Literature
  • BST 511: Topics in Statistical Inference I
  • BST 512: Topics in Statistical Inference II
  • BST 513: Analysis of Longitudinal and Dependent Data
  • BST 514: Survival Analysis
  • BST 516: Causal Inference
  • BST 523: Advanced Bayesian Inference
  • BST 531: Nonparametric Inference
  • BST 536: Sequential Analysis
  • BST 541: Multivariate Analysis
  • BST 550: Topics in Data Analysis
  • BST 570: Topics in Biostatistics
  • BST 582: Introduction to Statistical Consulting
  • BST 590: Supervised Teaching
  • BST 591: Reading Course at the PhD Level
  • BST 592: Supervised Statistical Consulting
  • BST 595: Research at the PhD Level