Teaching with Data for the Public Good


Materials for the JSM 2020 session "Teaching with Data for the Public Good"

View the Project on GitHub mine-cetinkaya-rundel/teach-data-public-good

Me, in previous life as University of British Columbia stats prof

Inside-Out Statistics | Bodwin

A well-reasoned, informal analysis is much better than a formal statistical analysis that lacks intuition.

“They might prefer imperfect solutions to ill-defined problems than perfect solutions to well-defined non-problems.” Gower discussing Cormack (1971)

Who’s Underrepresented? | Tackett

Difficult Dialogues | Hardin

General remarks and discussion points

The more applied, real-world the course, the more it exposed gaps in what I was a pro at. Not being the expert all the time. Is this more or less risky or rewarding if you already don’t meet the prof stereotype?

Risks vs. rewards of working with, e.g., data on COVID, slave trade, policing. One person’s topical is another persons lived experience. How do you do this with great empathy and humility? Also important to compare to realistic baseline: people weren’t 100% happy with the existing “tired” datasets, so you can’t expect to make everyone perfectly happy with new “read world” datasets either.