Services

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 or . We are currently accepting requests for Fall 2022. During the Fall 2022 semester meetings may occur remotely via Zoom or similar technologies or in-person. Request an in-person meeting if that's your preference. 

LISA Statistics and Data Science Zoom-in Hours (temporarily suspended in Fall 2022)

LISA is temporarily suspending our partnership with the Center for Research Data and Digital Scholarship (CRDDS) to conduct free Walk-in or Zoom-in hours to help researchers with statistics and data science every Tuesday noon-1PM and Thursday 1-2PM when classes are in session in the Spring and Fall semesters (not Summer).

  • Tuesdays, 12:00-1:00 pm in-person and via Zoom, Thursdays 1:00-2:00 pm Zoom only
  • If you would like to drop in on Tuesdays at Norlin E206, no registration is required.  to receive the Zoom link for online consultations on Tuesdays and Thursdays. If you are unable to attend our consultation hours and would like to set up a call, email crdds@colorado.edu.

Due to lack of personnel and funding, LISA is temporarily suspending our support for you to Walk in or Zoom-in to discuss your domain problem and get solutions to the statistical issues you are facing. ÍÃ×ÓÏÈÉú´«Ã½ÎÄ»¯×÷Æ·s are open to all researchers – from undergrad to faculty and beyond. Note: LISA assists with research, not class projects or homework.

Short Courses

LISA may or may not again teach our "Coding in R Workshop Series" with CRDDS to help researchers (especially graduate students) use statistics and R in their research. Recordings and materials for past courses, including our "Statistics in Python" short course series, are available on this website: View course list