University of Minnesota

School of Statistics' home page.

Expectations & Eligibility

Do I have to know any statistics?

Clients are not expected to already understand the statistical issues they face, or even to have any statistical background at all. Clients should be able to fully explain their experiment or study goals, and provide a basic overview of the issues involved.

Who is eligible?

All University of Minnesota faculty, staff, and students are eligible.

Researchers from the College of Education and Human Development (CEHD) and non-veterinary researchers in the Academic Health Center (AHC) will first be referred to the statistical consulting organizations within those units; the Office of Research Consultation and Services for CEHD and the Biostatistical Design and Analysis Center for AHC.

What kinds of projects are eligible?

Any project of scientific and educational research within the University of Minnesota is eligible for this service. Consulting is not available for questions regarding classwork or non-university projects or for general statistical software or database management support, except in the context of specific projects.

Where are you located?

We have offices on both Minneapolis and St. Paul campuses, in Ford Hall, and in McNeal Hall and the AS/VM building, respectively.

Do I have to come in-person?

Yes, our service is limited to in-person consultations made by appointment; walk-in, telephone, and email consultations are not available.

Who will help me?

To ensure consistent and high quality assistance, all projects are handled by a team of two consultants, always including one PhD level consultant.

What statistical software do you use?

The software we use in a particular case depends on both the statistical needs and the preferences of the individual researcher. We are most experienced with R, SPSS, SAS, and JMP, though have successfully worked with researchers using other software packages as well.

How do I recognize your work?

It is always appropriate to recognize the role of the Statistical Consulting Center in your research. This can range from a simple acknowledgement to co-authorship. Co-authorship is appropriate only when the consultant provides significant input to the final research product; it is not appropriate as a substitute for funding our service.

A statement of acknowledgement similar to the following may be appropriate: “The Statistical Consulting Center at the University of Minnesota and in particular [name the consultant] helped with the design and analysis of this experiment [or study or project].”

Articles: Please send copies of all articles that recognize the Statistical Consulting Center to, or by regular mail to Aaron Rendahl, School of Statistics, 313 Ford Hall, Minneapolis Campus.