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Is this a reasonable list of programs to apply to?

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A little about my experience:

Major: Math/Computing

GPA: a little north of 3.8

Research Experience: 2 Applied Math Summer REU's, both relevant to statistics

Course Experience: Linear Algebra, Real Analysis, Probability Theory, Stochastic Processes, Numerical Analysis, Mathematical Statistics, Linear Models, Programming in C++ and R, Statistical Computing, Monte Carlo Methods, Combinatorics, Graph Theory, Set Theory, Topology

GRE: haven't taken it yet

Programs I'm considering (all statistics unless noted)



Carnegie Mellon






NC State

Johns Hopkins

Ohio State



Princeton (ORFE)

My main concern is that it might be a bit top heavy or that it's a bigger list than it should be. Any thoughts? If you need more info, I can probably provide it.

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This may not be helpful at all, but my boyfriend had a very similar undergrad CV. His overall GPA was around a 3.9, GRE ~1400 on the old scale (800 quant, can't remember exact verbal score) and he had a few publications. Of the schools on your list, he applied to Carnegie Mellon, Hopkins, Yale, and NC State. He was accepted to NC State, and rejected by the others (not 100% sure about Hopkins, but definitely the other 2).

I'm not in your field, but my adviser suggested applying to about 10 schools to maximize chances of an acceptance without driving yourself completely insane, so the size of your list seems pretty doable. Of course, you should apply to schools where your and the program's/faculty's research interests mesh, and not just randomly add more in order to have more schools to apply to. Personally, I applied to all my schools in waves since they didn't all have the same application deadline. Fortunately, I was accepted before I had finished my final wave, so I just stopped.

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How did you go about picking these programs? I wouldn't add/remove based on selectivity or rankings so much as research fit. Yale is pretty small, for instance -- sure you want to bother with that one? I'd recommend starting a document where you go through each of these programs, list faculty whose research you find interesting, pick out any special features of the program that you like (e.g. formal concentrations), and then drop off any schools in which you struggled to find aspects that fit with your interests.

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I was mostly looking for places that seemed to be active in Machine Learning and Data Mining. I used the rankings at phds.org (with a focus on survey, research, funding and placement rate) to find programs, then I took out programs that didn't have many faculty that looked interesting (though I probably wasn't as systematic about it as I could/should have been). I didn't really look much at the specific requirements from program to program. At this point I'm not sure I'd know what I want for those types of things.

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I would recommend that you keep your options open and not cross any schools off purely based on perceived research "fit". First, it's usually difficult to find out enough about who's working on what to make a fully informed decision. And second, many PhD students end up working on something very different than they envisioned when they were applying to graduate school, and if that happens, you're better off at a place that provides lots of high-quality options (i.e. a top-tier institution).

Also, I think that list you have is pretty reasonable; if your letters and test scores are consistent with your academic record, I have a hunch that you won't need any additional safety schools.

Edited by cyberwulf
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