There are a number of forces that pull the field of Statistics in different directions, and perhaps some time ago "Frequentist vs Bayes" or even "Statistics vs Machine Learning" would have been major dichotomies to ponder and debate. But currently the balance between Theoretical and Applied Statistics is quite delicate, and it makes for an interesting discussion piece. This session will feature an all-star panel of Theoretical, Methodological, and Applied Statisticians. Some questions to be discussed and debated:
- What is the current balance between Theory and Applications in our field, in terms of how research is received / perceived / valued / rewarded?
- Has this balance changed in the last 20 years? 10 years? 5 years?
- Have we struck an optimal balance or are we moving in the wrong direction?
- What is the value of Theoretical work? The value of Applied work?
- What are some of the main challenges in today's Theory world? Applied world?
- What is the role of Computation and how does it fit in to all of this?