Testing, testing, is this thing right?

Abstract:
Quantitative approaches have a common concern: How can others be confident that our statistical models have been properly brought to bear on appropriate datasets? The key innovation presented in this talk is to integrate testing into the data science workflow. I will begin by describing what data science is, and one possible data science workflow. I will then discuss testing with regard to datasets and models.

Profile:
Rohan Alexander is an assistant professor at the University of Toronto, jointly appointed in the Faculty of Information and the Department of Statistical Sciences. He is also the assistant director of Canadian Statistical Sciences Institute (CANSSI) Ontario, a senior fellow at Massey College, a faculty affiliate at the Schwartz Reisman Institute for Technology and Society, and a co-lead of the DSI Thematic Program in Reproducibility. He holds a PhD in Economics from the Australian National University where he focused on Australian economic history. His book on foundational data skills, tentatively titled Telling Stories With Data, is available here: https://tellingstorieswithdata.com/