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University of Colorado Denver


Doctor of Philosophy


The PhD in Biostatistics prepares students for advanced study and research in biostatistics.  The program targets students with strong skills and training in mathematics and statistics who are interested in applications in health care and biological settings.

PhD Biostatisticians typically function as independent investigators or key collaborators and co-investigators with researchers in other areas.  In this function they take the lead in designing studies and analyses.  Many continue to teach and carry out research developing new statistical methods.  Areas of faculty research include analysis of longitudinal data, clinical trials, statistical methods in genetics and genomics, causal modeling, treatment of missing data and imputation, and power and sample size analysis.

Coursework (beyond the MS in Biostatistics) includes: advanced applied statistics; advanced theoretical statistics; and electives in a health care or biological area of the student’s choice.

For students with an MS in biostatistics or a related field the program can be completed in three to four years, with most of the first one to two years devoted to coursework and most of the later years to research and dissertation. Research and dissertation work involves developing, comparing and evaluating statistical methods (e.g. methods for analyzing data), typically motivated by an application in health care or biology.


Program Requirements - PhD Biostatistics





Required MS Biostatistics Courses



Elective MS Biostatistics Courses 



Required Public Health Courses



Foundations in Public Health

Public Health Elective

PUBH 6600




EPID 6630


Required PhD Biostatistics Courses


Advanced Mathematical Statistics I

BIOS 7731


Advanced Mathematical Statistics II

BIOS 7732


Elective PhD Biostatistics Courses

(Courses not listed require director approval)




Statistical Methods in Genomics

BIOS 7659


Analysis of Correlated Data

BIOS 7712


Statistical Methods for Missing Data

BIOS 7713


​Advanced Statistical Computing

​BIOS 7714


​Stochastic Modeling

​BIOS 7715


​Topics in Statistical Genetics

​BIOS 7716


Elective Health Sciences Courses




BIOS 8990






Core Competencies

  • Collaboration: Work collaboratively with biomedical or public health researchers on the design, implementation, data analysis, and dissemination of research studies.
  • Write or modify study aims so that the aims map to testable hypotheses.
  • Identify appropriate study designs and provide appropriate sample size justifications for study aims, and suggest new designs when existing approaches are inadequate.
  • Identify, implement, and correctly interpret appropriate data analysis approaches for study aims, and suggest new methods when existing approaches are inadequate.
  • Obtain basic understanding of biomedical or public health subject matter for collaborative project.
  • Establish and foster effective communication with non-statistician collaborators in written, graphical and verbal forms during the lifetime of the project.
  • Biostatistical Research: Develop and disseminate new biostatistical design, estimation, or hypothesis testing approaches.
  • Read (biostatistical literature on a subject area and synthesize the strengths and weaknesses of existing research.
  • Use statistical theory and biological/public health knowledge to propose new statistical methods to solve statistical problems deriving out of biomedical/public health research.
  • Use appropriate theory or design and implement appropriate simulation studies to exhibit that new methodology has sound statistical features.
  • Apply new statistical methodology to real data problems in biomedical or public health research.
  • Communicate effectively in written, graphical and verbal forms with biostatisticians.
  • Biologic or Public Health Relevance: Show how biostatistical tools apply to and influence research and policy development in the biomedical and public health arenas.
  • Read subject specific biomedical or public health literature and synthesize issues that are important in the design, implementation, and analysis of research in the subject area.
  • Identify areas in a specific biomedical or public health area where existing or new statistical approaches might transform the conduct of research or conclusions derived from research in that area.
  • Communication: Communicate and teach biostatiscal concepts to both biostatistical and non-biostatistical audiences.
  • Communicate orally and in writing simple and complex statistical ideas and methods to collaborators in non-technical terms.
  • Identify biostatistical knowledge and skills needed by collaborators, and develop materials to communicate that knowledge.
  • Identify biostatistical knowledge and skills needed by peers to understand a specific subject area, and develop materials to communicate that knowledge.

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