I read through the USWNR rankings for statistics grad schools and don't know if I understand the ordering. Ignoring biostatistics, the rankings look like:
Stanford
Berkeley
Harvard
University of Chicago
Carnegie Mellon
University of Washington
Duke
University of Michigan
Wharton
Columbia
NC State
As I am applying to Ph.D. programs for the fall 2021 cycle, I researched the departments. I will end up applying to almost all of these programs but wanted to ask the forum if my viewpoints make sense.
From what I have gathered, I do not get how Harvard is ranked so highly. The department is very small and largely focuses on two things, Bayesian inference and sampling, or design of experiments and causal inference. There seems to be one faculty member working on machine learning and given Ryan Adam's departure, it looks like they do not have much breadth at all in research areas. They do seem to have a large number of faculty in the biostatistics department, but that is a separate program all together (though I think it would be possible to work with these faculty quite easily).
Similar thoughts regarding University of Chicago. The department looks to be theory focused and more like an applied math department rather than a statistics department. They have a large fraction of faculty working on probability, PDEs, mathematical finance, etc. Only a small subset work on statistical methodology and theory. Given John Lafferty's departure, it also looks like they do not have much depth in ML.
If one were to re-do these rankings with a focus on ML, would it be correct to say, the top four should look more like Stanford, Berkeley, Carnegie Mellon, University of Washington?
