proctored a final this morning. grading tomorrow.
qualifying exam next thursday. two sections: methods and theory. methods is always a pain, since it is, essentially, just a grab bag of loosely connected stuff. theory should be fine, i just have to make sure i know the definitions and results of all the theorems. don't even need all the proofs!
starting next year, they've replaced the phd-level probability theory courses: it used to be 2 breakneck pace 4-credit courses, now it's a series of 3 3-credit courses, with the first course essentially being real analysis and measure theory. not much actual statistics-specific content in the first.
not sure what to take next semester. i have one open slot, was going to choose between stochastic processes and time series, but it turns out the wild theory guy who does the big data group is teaching nonparametric methods, which is way cool. or i could just work on research. choices. there's also always the temptation of the phd-level statistical computing class (mostly the theory of it), the continuation of the class i took this semester, but, glancing over the things they cover, i think i need more theory courses under my belt first - and it'd be too much to do that and the 2 phd core courses. i'll talk about it over the summer at some point with the instructor, as he's the guy i'm starting research with.
my head is leaking.
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