Collaboration

Our statistics and data science collaborators are trained to help design experiments, analyze and plot data, run statistical software, interpret results, and communicate statistical concepts to non-statisticians. Our assistance is free for University faculty, staff, and students on academic research projects. The collaborators are faculty and students in the Department of Applied Mathematics and other departments. The earlier in your research you request statistical advice, the better; so learn more about our collaboration service or Request a Collaboration Meeting. We are currently accepting requests for Spring 2021. During the Spring 2021 semester all meetings will occur remotely via Zoom or similar technologies.

LISA Statistics and Data Science Zoom-in Hours

LISA is partnering with the Center for Research Data and Digital Scholarship (CRDDS) to sponsor free Zoom-in hours to help researchers with statistics and data science every Tuesday noon-1PM and Thursday 12-2PM when classes are in session. Zoom-in hours require pre-registration. (We are doing this to prevent disruptive Zoom bombing.) You may register by completing a survey form for Tuesdays (noon-1PM) and Thursdays (noon-2PM). 

The Zoom link for Tuesdays' Interdisciplinary Data Consult Hours from noon-1PM will be sent to those completing this registration form.

The Zoom link for Thursdays' LISA Statistics and Data Scienec Zoom-in Hours from noon-2PM will be sent to those completing this registration form.

Zoom in to discuss your domain problem and get solutions to the statistical issues you are facing. Visits are open to all researchers – from undergrad to faculty and beyond. Note: LISA assists with research, not class projects or homework.

Short Courses

We are probably not teaching any short courses this semester as our university funding has run out and the path for university support for LISA is unclear. Recordings and materials for past courses, including our "Coding in R Workshop Series" with CRDDS to help researchers (especially graduate students) use statistics and R in their research and our "Statistics in Python" short course series, are available on this website: View course list