Oregon Health Sciences University (OHSU) and Portland State University (PSU) School of Public Health

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MS in Biostatistics

Program Overview

Program of Study

Core Competencies


The Master of Science in Biostatistics degree is designed to provide graduate level training in the application and theory of biostatistics. Students have the opportunity to do mentored work with faculty on ongoing health science research projects.

The program is aimed at those wishing to pursue careers as collaborative biostatisticians in the basic, clinical, translational or population sciences or who want to apply for doctoral programs in biostatistics. The program is also appropriate for some clinical and translational researchers, as well as working professionals throughout the state – including public health practitioners, laboratory scientists, data managers and database programmers, or for students who have earned a Graduate Certificate in Biostatistics and wish to pursue further training. Graduates are employed by local, state and federal agencies, health and medical centers, pharmaceutical companies and research institutions.

MS: Biostatistics Program of Study

Course Number Course Title Credits
Required Coursework (40 credits)
BSTA 510 Biostatistics Lab 3
BSTA 511 Estimation and Hypothesis Testing for Applied Biostatistics 4
BSTA 512 Linear Models 4
BSTA 513 Categorical Data Analysis 4
BSTA 514 Survival Analysis 3
BSTA 517 Statistical Methods in Clinical Trials 3
BSTA 519 Applied Longitudinal Data Analysis 3
BSTA 550 Introduction to Probability 3
BSTA 551 Mathematical Statistics I 3
BSTA 552 Mathematical Statistics II 3
PHE 511 Foundations of Public Health 3
  Epidemiology I (CPH, PHE, or PHPM section) 4
Elective Coursework (14 credits)
BSTA 500 Reading and Conference 1-3
BSTA 504 Special Topics in Biostatistics Variable
BSTA 515 Data Management and Analysis in SAS 3
BSTA 516 Design and Analysis of Surveys 3
BSTA 521 Bayesian Methods for Data Analysis 3
BSTA 522 Statistical Machine Learning and Big Data 3
BSTA 523 Design of experiment: Statistical principles of Research Design and Analysis 3
BSTA 524 Statistical Methods for Next Generation Sequencing Data 3
PHPM 513 Epidemiology II (Methods) 4
BMI 550 Computational Biology I 4
BMI 551 Computational Biology II 4
PSU STAT 567 Applied Probability 1 3
PSU STAT 568 Applied Probability 2 3
PSU STAT 580 Nonparametric  Methods 3
Comprehensive Examination (Pass/No Pass): written and lab sections

Students graduating from our program will be able to:

  • 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
  • Translate broad research goals into specifications and procedures for statistical analysis and interpretation of results in basic, clinical, translational and public health research studies
  • Select and use appropriate statistical analysis software for assessment, decision-making and information-sharing (e.g., Stata, SAS, R or other special programs)
  • Communicate statistical methods and findings clearly and unambiguously to specialists and non-specialist audiences

Application questions – Josh Hodsden, MBA

Registration questions – Laura Ehrlich, M.Ed.

Program Director – Rochelle Fu, PhD