How to Apply

All applications for statistics graduate programs are completed online using SLATE. The graduate program in statistics ordinarily grants admission for entry in the fall semester, entry in spring and summer is rare and only considered under special circumstances.

Any student applying for a PhD or MS in Statistics is also eligible to apply for the Data Science in Multi-Messenger Astrophysics training program. If you are interested, send an email to nrtmma_info@umn.edu and tell us in your personal statement why you are interested in the program. View more information.

The priority deadline for applications is December 15, 2022, although applications received after December 15 will be reviewed on a space available basis. The final application deadline is March 15, 2023.

The School of Statistics is pleased to provide graduate application fee waivers for entry in Fall 2023 to the first 90 applicants who are US citizens or permanent residents. Detailed instructions can be found at the link under “Application Fee” below. You must apply for this fee waiver ahead of time as we are not able to reimburse the fee once you have paid it.

No individual faculty has the authority to admit a student directly into the PhD program.  All applicants should go through the formal application process to be reviewed by the admission committee. After joining the PhD program, students find their thesis advisors under mutual agreement, which typically occurs during the first or the second year of the study.

To apply to our graduate programs, you must complete the SLATE online application. Materials to upload include:

  • Application fee 
  • Transcript
    • An unofficial transcript is required.
  • Three letters of recommendation
    • Acceptable recommendations will come from current or former professors who can assess your potential for graduate work. Other recommenders, such as employers, are also acceptable.
    • Paper copies are not accepted. 
    • Applications without three letters of recommendation may be rejected without review.
  • GRE scores
    • GRE scores are not required and there is no advantage to submitting them.
  • TOEFL (for non-native English speakers):
    • Our institution code is 6874. 
    • A TOEFL score of at least 79, with a reading subscore of at least 19 and a writing subscore of at least 21, is required.
    • IELTS may be substituted for the TOEFL. 
      • An IELTS of at least 7 with a writing subscore of 6.5 is required.
    • Please review the complete information regarding the TOEFL requirement.
  • Statements
    • Personal and description of research statements are required.
  • CV/Resume
    • A CV or resume is required.

Contact Information

Questions about your application should be directed to the office of graduate admissions, which can be reached by email at gsquest@umn.edu or by phone at 612-625-3014.

Further inquiries for the School of Statistics may be directed to apply@stat.umn.edu.

Frequently Asked Questions

  • We do not require a minimum GPA for applicants, though students are required to maintain a 3.0 or higher
  • We do not require a GRE score for fall 2023 admission
  • The School of Statistics requires a minimum TOEFL score of 79
  • IELTS may be substituted for the TOEFL
  • An IELTS of at least 7 with a writing subscore of 6.5 is required

The priority deadline for applications is December 15, 2022, although applications received after December 15 will be reviewed on a space available basis. The final application deadline is March 15, 2023.

  • Application fee, but be sure to investigate the options available to have your fee waived 
  • Transcript
  • Three letters of recommendation
  • TOEFL or IELTS (for non-native English speakers):
  • Research Description Statement
  • Personal Statement
  • CV/Resume

Yes. Personal statements and research description  statements are required for both the MS and PhD programs.

You do not need to submit any additional materials that are not listed here on the statistics website. 

Applicants may share whatever they feel is relevant to their application. There are no requirements or restrictions for length, format, or content.

We do not have any formal prerequisites. Nearly all successful applicants have familiarity with linear algebra and multivariable calculus. Additional background in statistics, mathematics, computer science, or some other related area is also common. 

You need three letters of recommendation.

Yes, you need to submit an unofficial transcript.

We understand that the deadline for admission is earlier than when you receive your fall term grades, and we do not expect every applicant to have those grades yet.

A strong mathematics background, especially in probability, statistics and linear algebra, is important in the admission process. However, it is not the only factor that determines which applicants are admitted. If such is the case, it is strongly suggested that prospective applicants consider strengthening their math skills and apply later.

We will be unable to determine your chances of admission outside of the application system. 

We matriculate approximately 20 students to the MS program and 8-10 PhD students each year.

We may have a few teaching and research assistantships available each term, but please do not apply based on this, as we cannot guarantee support. 

Our graduate programs take place in person and on campus. Online courses are not offered at this time.

Many students work part time (5-20 hours a week) while pursing an MS or PhD degree in our programs, but the answer to this question will depend on your individual work arrangement. Here are some factors that may help you decide what is feasible for you: 

  • Most classes for our MS and PhD programs are held during the daytime, and attendance is required. 
  • Students must take between 6-14 credits per semester. 
  • For each credit taken, students spend approximately 2 hours studying outside of class. So if you take 6 credits, you can expect to spend roughly 12 hours per week studying for those credits, in addition to any time spent in class.