Statistical Consulting and Research Services
Welcome to the Statistical Collaboration and Research Services (SCRS - pronounced "scissors")! SCRS is currently funded almost entirely by Montana INBRE, CAIRHE, AI-AN CTRP, Mountain West CTR-IN and investigators associated with these grants are given priority. If resources allow, we offer statistical collaboration to MSU students, faculty, and non-affiliates.
We offer assistance and collaboration through the entire research process, including general discussions regarding the role of statistical inference in your research:
- Research Planning/Design: Refining of research questions and objectives; study design (experimental, sampling, survey, observational, …); analysis planning; planning for data organization and management; assistance with developing research proposals; etc.
- Analysis: Aligning statistical methods and models with research questions and design; exploratory data analysis and creative visualization of data; assistance in understanding and translating assumptions underlying models and methods; interpretation of statistical results.
- Dissemination: Assistance with graphical and tabular displays of data and analysis results; interpretation of results in the research context; wording related to design, methods, analysis, and interpretation; writing about statistical inference used in the research; communicating about the benefits and limitations of the use of statistics in scientific research; etc.
The level of involvement can range from a few hours of assistance to long-term collaborations resulting in co-authored publications. The depth and extent of collaboration is developed on a case-by-case basis depending on the project, researcher requests, statistician availability, and funding. Our funding sources must be acknowledged in publications and presentations for any amount of effort. Please see our Frequently Asked Questions page for answers to common questions.
For questions about expectations and details regarding payment for services, please contact Mark Greenwood directly.
To request statistical consultation, please submit a Request Form. Please fill out the form as soon as you think you may want to work with us, preferably early in the research process before the design is finalized and data are collected. We are currently not taking on new collaborations unless you are associated with the NIH IDeA program grants listed above. We apologize for this, but simply do not have the bandwidth to cover all requests. We also encourage you to still submit a request form to help us demonstrate demand for statistical collaboration at MSU. Thank you for your understanding and patience.
Interim Director: Dr. Mark Greenwood
Current Advisory Council: Alexandra Adams, Ann Bertagnoli, James Burroughs, Michele Hardy, Andrew Hoegh, Kathryn Irvine, Sara Mannheimer, Tricia Seifert, Jovanka Voyich-Kane
Past Advisory Council Members: John Borkowski, Steve Cherry, Mike Franklin, Mark Greenwood, Megan Higgs, Mary Leonard, Andrea Litt, Scott Myers, Donna Williams
Current Statisticians (Summer 2019): Lisa Bowersock and Tan Tran
Current Undergraduate Intern: Jaley Priddy (Hilleman Scholar)
Past Directors, Associates, and Consultants: Christopher Barbour, Katharine Banner, Noah Benedict, Kenneth Flagg, Bridgett Foran, Leslie Gains-Germain, Megan Higgs, Michael Lerch,Lillian Lin, Andrea Mack, Maya Marchese, Sarah McKnight, Elizabeth Mery, Christopher Peck, Michaela Powell, Claire Rasmussen, Laurie Regemer, Jordan Schupbach, Jeremy Tate, Allison Theobold, Stephen Walsh, Jennifer Weeding, Huafeng Zhang
Statistical Consulting Seminar: Graduate students in Statistics take the hands-on Statistical Consulting Seminar Course (STAT 510) as a part of their graduate program. SCRS and the Statistical Consulting Seminar work together to provide consulting services to clients through this class. Typically, the Statistical Consulting Seminar serves graduate students in other departments (as the clients) who are willing to work through the slower and free-of-charge process offered through this avenue. This is a great opportunity for graduate students from different departments across campus to participate in cross-disciplinary collaboration (the course is for Statistics graduate students).