My toolbox is full of shiny tools, do I also need superpowers?

Mine Çetinkaya-Rundel (Duke University / RStudio)


Over the past decade the number of different computational tools our students encounter throughout their undergraduate education has increased greatly. But having a toolbox full of shiny tools is not sufficient for the modern student to be a productive statistician or data scientist. The modern student needs to learn to use these tools in harmony with each other. And unlike superheroes that tend to be good at using one superpower well, the modern student needs to have practical familiarity with many "superpowers". In this talk, I'll talk about how to integrate various superpowers into statistics and data science curricula, e.g., shapeshifting (data manipulation), clairvoyance  (predictive modeling), replication (reproducibility), time travel  (version control), and perhaps most importantly empathy, as "with great power comes great responsibility".