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Biostatistics MA

Many issues in the health, medical and biological sciences are addressed by collecting and exploring relevant data. The development and application of techniques to better understand this data is the fundamental concern of our program. We offer training in statistics and biostatistics theory, computer implementation of analytic methods, and opportunities to use this knowledge in areas of biological and medical research.

Berkeley Public Health and UC Berkeley’s Department of Statistics, together with other UC Berkeley departments, offer a broad set of opportunities to satisfy the needs of individual students. In addition, the involvement of faculty from UCSF’s Department of Biostatistics and Epidemiology enriches our instructional and research activities.


Our master’s program is a two-year program consisting of 48 units with courses selected from biostatistics and statistics, public health, and biology.

The oral comprehensive examination is designed to test a candidate’s breadth of understanding and knowledge, as well as the ability to articulate and explain the basic concepts gained from the curriculum. Alternatively, a thesis may be submitted to fulfill requirements. However, the decision to submit a thesis rather than take the oral examination must be made early in the final semester of the program.

Students should take the following courses:

  • STAT 201A: Introduction to Probability at an Advanced Level
  • STAT 201B: Introduction to Statistics at an Advanced Level
  • PH C240A: Introduction to Modern Biostatistical Theory and Practice

In addition to Statistics 201A and 201B and PH C240A, students are expected to take PH252D (Introduction to Causal Inference) and at least two other courses from the following list:

  • PH C240B: Biostatistical Methods: Survival Analysis and Causality
  • PH 240C: Computational Statistics
  • PH 252E: Advanced Topics in Causal Inference
  • PH 244: Big Data: A Public Health Perspective
  • CS 294.150: Machine Learning and Statistics Meet Biology
  • PH C242C: Longitudinal Data Analysis
  • PH 290.X: Targeted Learning in Biomedical Big Data


Previous coursework in calculus, linear algebra, and statistics is strongly recommended.

Common undergraduate majors for admitted applicants: Biomedical & biological sciences, mathematics, statistics. Common work experience for admitted applicants: Typical successful applicants have work experience in Research Assistant positions at a health department.

GRE Exemption Criteria

GRE General Test scores are required for admission to the Biostatistics MA program however applicants are exempted from the requirement if they meet all of the following criteria:

  • Completed two semesters of calculus for a letter grade and earned a grade of “B” or higher.
  • Completed one semester of linear algebra for a letter grade and earned a grade of “B” or higher.
  • Completed one semester of statistics for a letter grade and earned a grade of “B” or higher.
  • Cumulative undergraduate GPA of 3.0 or higher.
  • Overall quantitative/math GPA of 3.0 or higher.
  • For international students: TOEFL score of 100 or higher OR IELTS score of 7.0 or higher

Berkeley Public Health also exempts applicants who already hold a doctoral level degree from the GRE requirement.You can find more information on the application instructions page. There is a program page in the Berkeley Graduate Application where you can indicate you meet the criteria for GRE exemption. Applicants who are exempted from the GRE are not at a disadvantage in the application review process.


Some students pursuing the MA degree intend to continue directly into a PhD program, while others take research positions in tech companies, federal agencies, state and local health departments, health care delivery organizations, and private industry. MA students interested in continuing into the UC Berkeley Biostatistics doctoral program immediately following their MA degree should apply to the new degree program through the Online Application for Admission during their second year of study during the normal admissions cycle.

Funding and Fee Remission

Prospective students who are US citizens or permanent residents can find more information about applying for an application fee waiver for the Berkeley Graduate Application. Fees will be waived based on financial need or participation in selected programs described on the linked website. International applicants (non-US citizens or Permanent Residents) are not eligible for application fee waivers.

  • More information about funding and fee remission

    Some MA and MA/PhD admitted students are made a funding offer as a part of their admission package. These offers depend on funding availability and the applicant pool for that year.

    Tuition and fees change each academic year. To view the current tuition and fees, see the fee schedule on the Office of the Registrar website (in the Graduate: Academic section).

    Please contact if you have any questions about funding opportunities for the biostatistics programs.

Diversity, Equity and Inclusion

The Division of Biostatistics is committed to challenging systemic inequities in the areas of health, medical, and biological sciences, and to advancing the goals of diversity, equity, and inclusivity in Biostatistics and related fields.

Diversity, Equity and Inclusion in Biostatistics

Admissions Statistics


Admissions Ratio (19/145)


Average GPA of admitted applicants


Average Verbal GRE percentile


Average Quantitative GRE percentile


Average age upon admission


Average years of professional/research experience

Faculty Associated in Biostatistics Graduate Group

  • Peter Bickel PhD
  • David R. Brillinger PhD
  • Perry de Valpine PhD
    Environmental Science, Policy, and Management
  • Haiyan Huang PhD
  • Michael J. Klass PhD
  • Priya Moorjani PhD
    Molecular & Cell Biology
  • Rasmus Nielsen PhD
    Integrative Biology and Statistics
  • Elizabeth Purdom PhD
  • Sophia Rabe-Hesketh PhD
  • John Rice PhD
  • Yun S. Song PhD
    Statistics; Electrical Engineering and Computer Sciences
  • Bin Yu PhD