Graduate SDEs and Real analysis

[deep_lazy]

I used to study in a math department (undergraduate) where most people who were preparing for grad schools were mostly aiming math phds.

Most of them who were planning to study analysis have taken graudate real analysis (Rudin RCA or equivalent depending on the professors preference) and measure theory based stochastic calculus (the main goals is to prove the existence of the solution of SDEs).

I dont know much about stat people in my school so it's unclear for me whether these advanced analysis courses are frequently taken by people aiming stat or biostat phds.

How is it like based on your personal experiences? I would be greatful to listen to your thoughts.

Edited June 17, 2019 by deep_lazy
additional info

[Stat Assistant Professor]

Among international applicants, it seems as though the majority of the competitive applicants have taken at least measure theory. If you went to a top school like Oxbridge, Peking, Tsinghua, etc. and majored in math/stat, it probably isn't unusual for you to have taken graduate-level (in the U.S.) real analysis as an undergrad. I'm not sure about stochastic differential equations, though -- probably the students who are especially interested in quantitative finance have taken a class on stochastic calculus. 

Among domestic applicants, it is rarer for applicants to PhD programs in Stat or Biostat to have taken these courses. But in my opinion, it is not that important to know measure theory before entering grad school in Stat (or math), as they'll teach you what you need to know during the coursework phase of the program.

Edited June 17, 2019 by Stat PhD Now Postdoc