Theoretical statistics is the theory of applied statistics: how to think about what we do
Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University
Working scientists and engineers commonly feel that philosophy is a waste of time. But theoretical and philosophical principles can guide practice, so it makes sense for us to keep our philosophical foundations up to date. Much of the history of statistics can be interpreted as a series of expansions and inclusions: formalizations of procedures and ideas which had been previously considered outside the bounds of formal statistics. In this talk we discuss several such episodes, including the successful (in my view) incorporations of hierarchical modeling and statistical graphics into Bayesian data analysis, and the bad ideas (in my view) of null hypothesis significance testing and attempts to compute the posterior probability of a model being true. I’ll discuss my own philosophy of statistics and also the holes in my current philosophical framework.
It’s happening at 3pm Friday 10 Feb, in Michigan League – Kuenzel Room, and it’s the Foundations of Belief & Decision Making Lecture, organized by the Philosophy Department.