That didn't really come up. We were doing institutional research for a university to support senior leaders. Most of our work entailed working with transactiona

That didn't really come up. We were doing institutional research for a university to support senior leaders. Most of our work entailed working with transactional HR data, educational outcomes data, other information collected at the university to provide policy analysis and strategic recommendations. The stats and econ phd came from the same school, so they had more shared vocabulary, but definitely thought about problems differently. The physics colleague came from Europe and also thought about problems at a much different scale. So a lot of the initial time was spent deriving proofs so that everyone felt comfortable with different statistical methods used for analysis. The data we worked with was often small scale, sparse, and not really IID. The proofs all essentially converged, but it was interesting because different language and assumptions were made depending on their distinct disciplinary backgrounds. Sorry for the vague speak. A lot of the work we did was confidential, so can't really talk specifics.