What We Do
Statistical consulting is free to all members of the UMD research community (undergraduate and graduate students, faculty, staff), in all departments and disciplines. Research is increasingly data-driven, and we are available to answer your statistics and analysis questions through email or an in-person consultation. We currently specialize in SAS, SPSS, R, and can also provide support on Survey Design and Analysis. We may also refer you to a software specialist as needed. Our mission statement contains information on the overarching goals of our services.
Questions and Appointments
We are now open for 2018 Spring semester. Our statistical consulting service is available:
- Mon: McKeldin 11:00 - 16:00
- Tue: McKeldin 11:00 - 16:00
- Wed: McKeldin 11:00 - 16:00
- Thur: STEM 11:00 - 16:00
The consultations are by appointment only. Click on the button on the left to schedule. Serving your needs might require multiple consultations. If you have any questions about our service, contact us by emailing firstname.lastname@example.org.
Examples of services we provide:
- Explaining statistical concepts
- Selection of statistical procedures
- Use of statistical software
- Data clean and analysis
- Interpretation of results
- Research design
- Survey design and sampling method
Examples of services we do not provide:
- Collecting, preparing, or writing up data for researcher
- Explaining highly technical or advanced statistical questions
- Tutoring for statistical homework (math tutoring resources)
Statistical software workshops
In addition to one-on-one consultations, we also offer statistical software workshops on common statistical packages. Click here to know more about upcoming workshops. Subscribe to our mailing list to be the first ones to get notification when a workshop is available!
Disclaimer: The following external links are for informational purposes only. They do not constitute an endorsement by the UMD Libraries. UMD Libraries do not bear responsibilities for the accuracy, legality or content of the external links.