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Program Information

Program/Department Chair: Dongseok Choi

Authorized Award(s): M.S., M.B.ST., Graduate Certificate

Minimum number graded credit hours: 48, M.S./M.B.ST.; 30, Graduate Certificate

 

Program Purpose Statement

The mission of the Division of Biostatistics is to improve the health of the public by incorporating Biostatistics into public health, clinical medicine and basic sciences by providing biostatistics leadership and expertise in interdisciplinary research; educating students in theory, methods and applications in Biostatistics; advancing statistical methodology in biomedical research; and training a board range of biomedical researchers in biostatistical concepts and applications.



Student Learning Outcomes

Upon successful completion of the Graduate Certificate Program, students will be able to: 

  1. Perform a broad range of basic and intermediate level applied statistical procedures that are required in basic, clinical, population and translational sciences.
  2. Interpret and summarize analysis results in research reports and papers and communicate them to individuals with varying degrees of statistical knowledge.
  3. Apply the principles of research design to address problems in basic, clinical and population sciences.
  4. Identify strengths and weaknesses of alternative designs and analytic methods.
  5. Conduct analyses for the student's own research projects or provide support to collaborative research teams.

 

Upon successful completion of the M.S. in Biostatistics Program, students will be able to: 

  1. Apply intermediate to advanced biostatistical theory and techniques to design, plan and manage data collection to conduct analysis for own research projects or support collaborative research teams.
  2. Translate broad research goals into specifications and procedures for statistical analysis and interpretation of results in basic, clinical, translational and public health research studies.
  3. Select and use appropriate statistical analysis software for assessment, decision-making and information-sharing (e.g., Stata, SAS, R or other special programs).
  4. Communicate statistical methods and findings clearly and unambiguously to specialists and non-specialist audiences.