MS in Biostatistics
Please visit our MS Admissions Page for detailed application instructions.
MS IN BIOSTATISTICS PROGRAM SUMMARY
The Master of Science in Biostatistics degree program at OHSU is designed to provide graduate level training in the application and theory of biostatistics. The program is primarily aimed at those wishing to pursue careers as intermediate level biostatisticians or apply for doctoral programs in Biostatistics. The program is also appropriate for individuals who have earned a Graduate Certificate in Biostatistics and wish to pursue further training.
Target audiences for this program include individuals who desire careers as collaborative biostatisticians in the basic, clinical, translational or population sciences. The program will also be appropriate for some clinical and translational researchers (e.g. K awardees or postdoctoral trainees), students in other Oregon graduate programs, as well as working professionals throughout the state and region (e.g. public health practitioners, laboratory scientists, data managers, database programmers, other research professionals).
All faculty members in the Department's Division of Biostatistics are actively involved with externally funded projects. Students will have opportunities to work with real world applications under the supervision of faculty. To learn more about our faculty and their research, please visit the Biostatistics Division's web page.
All OHSU graduate programs are accredited by the Northwest Commission on Colleges and Universities.
Graduates of 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.
PROGRAM REQUIREMENTS (48 credits total)
Forty eight (48) credits will be required to earn the M.S. degree. After completing the 48 credits, a comprehensive exam is required. The programs will include formal didactic sessions and hands-on statistical computing training.
Required courses (33 credits):
BSTA 510 Biostatistics Lab – 3 credits
BSTA 512 Linear Models – 4 credits
BSTA 513 Categorical Data Analysis – 4 credits
BSTA 514 Survival Analysis – 3 credits
BSTA 519 Applied Longitudinal Data Analysis – 3 credits
BSTA 517 Statistical Methods in Clinical Trials – 3 credits
BSTA 550 Introduction to Probability - 3 credits
BSTA 551 Mathematical Statistics I- 3 credits
BSTA 552 Mathematical Statistics II - 3 credits
Electives (15 credits):
BSTA 500 Reading and Research in Biostatistics - 1-2 credits
BSTA 504 Topics in Biostatistics - 3 credits
BSTA 515 Data Management and Analysis in SAS – 3 credits
BSTA 516 Design and Analysis of Surveys – 3 credits
BSTA 521 Bayesian Methods for Data Analysis – 3 credits
BSTA 531 Lean & Six Sigma I - 3 credits
BSTA 532 Lean & Six Sigma II - 3 credits
Electives from other programs:
PHPM 512 Epidemiology I – 4 credits
PHPM 513 Epidemiology II (Methods) – 4 credits
BMI 550 Computational Biology I – 4 credits
BMI 551 Computational Biology II – 4 credits
PSU: Applied Probability 1 – 3 credits
PSU: Applied Probability 2 – 3 credits
PSU: Modern Nonparametric Statistics – 3 credits