We’re pretty open-minded about where talented students can come from and have admitted students from a number of non-stat or math undergraduate majors (biology, psychology, journalism, etc.). What matters is that they have the appropriate mathematical and statistical preparation from taking the prerequisites.

The acceptance rate for students applying to the MS program is generally above 60%.

The admissions committee reviews applicants according to their record of academic achievement, demonstrated academic potential, letters of recommendation, background and experience, and other factors. GPAs provide competitive points of reference for admission but are not alone decisive in the admissions review.

If your goal is to obtain a PhD in Biostatistics, we encourage you to apply directly to the PhD program, even if you don’t already hold a master’s degree. If you are not admitted to the PhD program and do not hold a previous master’s degree in statistics or biostatistics, you will be considered for admission to the master’s program if you indicate your interest in your SOPHAS application.

We are unable to pre-review applications for admission.  All applications reviewed must be received from the centralized application company, SOPHAS.

View information about the Biostatistics programs.

If you are only applying to the PhD program in Biostatistics at the University of Minnesota, you can send copies of your international transcript(s) and degree conferral directly to the University of Minnesota School of Public Health via e-mail to sph-ask@umn.edu.  Students who are admitted to the Biostatistics PhD program will, upon matriculation, be required to provide a WES ICAP document-by-document evaluation of academic credentials directly to the University of Minnesota School of Public Health.

If you wish to be considered for the MS in Biostatistics (or if your application is not accepted into the PhD program and you wish to be considered for MS admission), a WES evaluation is required at the time you submit your application to SOPHAS to consider your application complete.

Students are able to complete the master’s program as a part-time student.  All requirements for the master’s degree must be completed and the degree awarded within five calendar years after initial enrollment in the graduate program.

Our master’s program is not available as an online degree, and it does require full-time (12-14 credits/semester) attendance if you want to complete the program in 2 years.  Depending on the courses, students are required to be on campus 2-5 days/week.

Master’s students work on a Plan B project, which can lead to a published paper. Plan B projects have been published in the past.

Our faculty are involved in many areas of methodological and collaborative research in areas including, but not limited to, clinical trials, statistical genetics, machine learning, and biomedical imaging. MS student research is in close collaboration with our faculty and potentially other collaborators, and thus the potential research areas are very broad.

Get comfortable with taking derivatives and evaluating integrals, especially if you took calculus a long time ago. Same for linear/matrix algebra, which will be important for the second-semester coursework.

Most graduate students use R, so you could prepare by learning the basics of R and Rmarkdown (Datacamp has a free Intro to R class), but this is not necessary. Many graduate students take an introductory R class their first semester.

If you have no exposure to LaTeX, you can save yourself some time by learning the basic mechanics before classes start, for example through tutorials from Overleaf.

Our faculty are involved in many areas of methodological and collaborative research in areas including, but not limited to, clinical trials, statistical genetics, machine learning, and biomedical imaging. MS student research is in close collaboration with our faculty and potentially other collaborators, and thus the potential research areas are very broad.

If you have not completed the prerequisites at the time you are applying, tell us your plan for completing the prerequisites in your Statement of Purpose and Objectives. This can be a sentence describing where you’ve enrolled (e.g. university, community college, Coursera) and when they will be complete.

Admission into the Biostatistics program is competitive.  Depending on the applicant pool, it is in an applicant’s best interest to have completed (or be in the process of completing) prerequisites at the time they submit their application for review to the committee. If an applicant has completed all of the other course prerequisites and only has one course in progress remaining, the committee usually will have an idea how the student will do based on their previous coursework.

The Division of Biostatistics & Health Data Science is unable to review applications for admission until we have received the complete application (including all required transcripts, letters of recommendation, statement of purpose, etc.).

The complete process for applying to the PhD program while you are in the MS program can be found in our student guidebook (PDF).

For students currently in our Biostatistics program who apply to the PhD program, they will find all of their information will still be available in SOPHAS/WebAdmit.  The student does not need to resubmit transcripts (unless information has been updated since their last application was submitted).  In addition, internal applicants only need to submit 2 letters of recommendation (both from the University of Minnesota). Admission isn’t guaranteed, but those students who have taken the appropriate PhD prep coursework (i.e. STAT 8101/8102 and real analysis) and performed well in the courses have a strong chance of admission.

We are unable to guarantee funding (RA or TA positions) for our master’s students.  Some first year MS/MPH students receive partial funding; many second year MS students receive at least partial funding. Some of our students find graduate research positions elsewhere on campus, usually as a statistical programmer, to support them while they complete their Biostatistics MS/MPH degree. These positions are posted on the University of Minnesota employment page. If University departments forward Graduate Position announcements to the Biostatistics Division, we forward the information directly to all of our students.

Careers are available in academic, governmental, non-governmental, and private industry settings. Recent graduates have been hired at publicly funded research institutions including: Fred Hutchinson Cancer Research Center, University of Texas, Stanford University, the Food and Drug Administration, and also at private companies including St. Jude Medical, Eli Lilly, Boston Scientific, Medtronic, Merck, 3M, and Affymetrix. Of our MS students who graduated between 2018 and 2020, 58% were employed in the private sector, 20% as a statistician affiliated with a university organization, and 22% enrolled in a PhD program.

A degree in biostatistics provides broad technical training that is marketable to a broad range of employers, leading to a wide range of potential jobs. Of our MS students who graduated between 2018 and 2020, for those who were employed in the private sector or are affiliated with a university organization, job titles include Statistical Programmer, Statistical Modeling Consultant, Data Scientist, Software Developer, and Biostatistician.