What we do
- Answer your statistics and analysis questions through:
- Virtual consultation using Zoom
- In-person consultation at STEM library
- Email: email@example.com
- We currently specialize in SAS, SPSS, R, and can also provide support on Survey Design and Analysis.
- We do NOT tutor on statistical classes or homework.
Got a statistical question?
Research is increasingly data-driven, and we are available to answer your statistics and analysis questions! If you have a question, click the schedule appointment button below!
- 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
Frequently Asked Questions:
What is the cost?
This service is free to all members of the UMD research community (undergraduate and graduate students, faculty, staff), in all departments and disciplines.
Can you help me with my statistical classes and/or homework?
No. For help on statistical homework, please visit math tutoring resources.
Can you collect, prepare, or write up data for me?
Can you explain highly technical or advanced statistical questions?
Where are you located?
We take appointments in McKeldin Library and the STEM Library.
Introductory Statistical Resources
You can find answers to your statistical questions through these frequently asked questions.
Review these resources on common statistical topics to get you started:
Data Analysis and Visualization
Introduction to Regression
- Linear Regression
- Multivariate Regression
- Logistic Regression
- Regression using SAS
- Probit Regression
- Cox Regression
- Logistic Model
- Cox proportional Hazard Model
- Probit Regression Model
- Loglinear Model
- Generalized linear Model
- Multilevel Model
Statistical software workshops
In addition to one-on-one consultations, we also offer statistical software workshops on common statistical packages. Learn more about our upcoming workshops and 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.
The Statistical Consulting Service offered by the University of Maryland Libraries provides assistance to the campus research community, via email and through in-person consultations. Guidance is available in the following areas:
- Statistical software programs, such as SPSS, SAS, or R
- Survey design
- Finding and using data sources
- Explaining common statistical methodology
- Data manipulation and analysis techniques
- Basic interpretation of results
Value added to University Community
Lowering research barriers by increasing statistical awareness. Data-driven research is becoming the norm, even in traditionally non-quantitative disciplines. Across all disciplines, finding, collecting, storing, and sharing data is a challenge. Also, investigators can and do struggle to keep abreast of the newest statistical and analytical techniques. Statistical consulting services can increase statistical and programming literacy, allowing researchers to focus on the big picture rather than getting bogged down by the details.
Developing workshops to teach programming fundamentals. Researchers are expected to be self-learners. Preparing study data and learning to code is time consuming, but introductory workshops get investigators moving quickly. We offer instruction in basic programming, data manipulation, analysis, and summarization of results in figures and tables in statistical software languages to the general University of Maryland research community.
Fostering interdisciplinary collaboration by serving as middle ground. Statistical tools and techniques vary across academic disciplines, a hurdle to collaboration. Statistical consulting services can unify understanding of techniques and bring together researchers. The Libraries can serve as a center for researchers who are otherwise scattered across campus, fostering innovation and interdisciplinary work.