mathsimp

While its not as drastic as comparing physics and chemistry, they definitely are two focus areas. For example, there are quite a few biostats departments that do a lot of work in causal inference, while in statistics, the focus in causal is not as strong. I think the onus is on the applicant to figure out which program is a better fit ultimately.

couple things that i have noticed different from the 2018 rankings that may be worth pointing out, and these things may or may not be true 1) the number of schools being ranked increased by a lot, 101 schools in statistics only, and 65 biostats schools. I believe in 2018, it was close to 90 schools biostats and stats combined. 2) the statistics rankings did not move for the most part from 2018. schools fell and rose, but nothing really went down a lot, nothing really went up a lot, relatively speaking. schools like JHU which was previously ranked in 2018 are no longer ranked on this list, possibly for reasons as bayessays listed. also, the last time rankings came out was in 2018 as mentioned, and now its 2022. in other disciplines, it seems that they were ranked more frequently. Any idea why rankings come out less frequently in (bio)statistics or am I just imagining things?

Long time lurker here - I'm currently at a mid ranked PhD program in statistics and just about to start my second semester of my first year (wrote my apps in 2020 for admission for fall 2021). Between the time I was admitted and now, I feel I am more interested in more theoretical and abstract mathematics such as measure theory, functional analysis, topology, probability theory, and stochastic processes - as opposed to machine learning, data science with biological applications (which were my original interests that led me to statistics). Our department has maybe about 2 faculty, out of 10 or so who seem to produce students who do work in the area remotely related to what I am interested in. However, in our (applied and pure) math department has maybe 5 faculty publishing in this area in journals such as Annals of Probability and of the such. I suppose having a few of them on my committee would be a good idea, however I have been told that these faculty are swamped with their own students and is unlikely to take students from outside their department. Despite all this, my end goal is to be in quantitative research, probably in the industry as opposed to academia. I'm concerned that I may not be able to do my research I am interested in my own department. There are three routes in my opinion, in the order of least to most time consuming: 1) Go through with the statistics PhD and try to align my research as close to what I originally hope it to be 2) Reapply to PhD programs that have a stronger emphasis on the mathematical side. 3) Drop out, get a masters in (applied)math for the letters, and apply for applied math or pure math programs Is there anything else I can do to be able to study more math, specifically stochastic analysis as a culmination of topology, measure theory, and functional analysis? Perhaps staying in a statistics program can help me apply stochastic processes to machine learning algorithms or population biology - which would be interesting and we have faculty working in this area, but I'm hoping the meat of my research is still going to be more about the math behind it. My profile for reference: BA: Economics @ Ivy League (CGPA: 3.5) Relevant courses: Calc 1,2,3 (A,A,A+), Linear Algebra (A-), Probability (A), Inference (A-), Mathstat (A), Regression (A), Real Analysis I, II (A, A-) - included measure theory MS: Statistics @ Large State School (ranked 35-45) (CGPA: 4.0) PhD Statistics @ Mid ranked department (ranked 40-50) (CGPA 4.0 - does this really even matter at this point though?) Any advice from current faculty or grad students is greatly appreciated.