Training Interdisciplinary Statistical Collaborators: A Comparative Case Study Journal Article uri icon



  • Abstract; Statistics is an inherently collaborative discipline as individuals across academia, government, and industry all rely on data to answer relevant questions and innovate in their fields. As a result, there is a growing body of research regarding how to teach interdisciplinary collaboration skills to statistics students. However, much of this work relies on data that do not objectively assess collaboration. Additionally, prior research lacks detailed evidence of how to assess quality of collaboration skills. In this case study, we compare the statistical collaboration skills of both a team of students and an expert collaborator on two components of effective statistical collaboration: structuring a statistical collaboration meeting and communicating with a domain expert during a statistical collaboration meeting. We find that students can facilitate meetings and communicate comparably well to an expert statistical collaborator, but that expert collaborators may be better able to facilitate meetings and communicate to develop strong relationships with domain experts, an important element for high-quality and long-term statistical collaboration projects. Further work is needed to generalize these findings to a larger population, but these results begin to inform the field regarding effective ways to teach specific statistical collaboration skills.

publication date

  • August 18, 2022

has restriction

  • green

Date in CU Experts

  • August 30, 2022 3:22 AM

Full Author List

  • Alzen JL; Trumble IM; Cho KJ; Vance EA

author count

  • 4

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