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Geococcyx last won the day on June 29 2019

Geococcyx had the most liked content!


About Geococcyx

Profile Information

  • Location
    Research Triangle
  • Application Season
    2019 Fall
  • Program
    Stat & Biostat Ph.D.'s

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  1. In general, you shouldn't consider no response a rejection so early. Maybe not immediately, but if some folks turn down interviews, then they may invite more to keep similar numbers of interviewees. Alternatively, if enough people turned them down after interviews then they may look at the top people they didn't invite out. Those are possible even if they hope to interview anyone they're interested in and they invite everyone at once, which as you note aren't necessarily the case.
  2. I think(?) you'd want to go through the director of graduate studies rather than the admission committee, but you're welcome to ask them. I should note for anyone else that unless the school specifically asks for your fall grades, you don't need to send them, so it's only really worth sending fall grades if they're to your benefit.
  3. It's probably a little lower than where you're aiming, but I think Duke stat has good people in TDA (Sayan Mukherjee) and privacy research (Jerry Reiter), although my lack of knowledge of differential privacy makes the second point a bit speculative.
  4. Yeah, you'll get in somewhere -- as I recall, Virginia's just a small program, so they're harder to get into (just like NYU, Northwestern, Brown biostat, etc.) because of their small size. I got into Illinois last year without taking the Math GRE, with roughly the same math background from a worse university. There's no reason to take the Math GRE unless you're applying to Stanford. Maybe it helps at Columbia, UChicago, and UC Berkeley, but I know the first two accepted people last year who didn't take it, so it's not a big deal. Bayessays posted while I was writing, and they are correct about your chances. I think you should apply a little above Duke, and maybe a little above CMU, but I do usually suggest people apply higher than bayessays does -- that's your choice, and ultimately is a factor of how much money you have lying around to throw at applications. In any case, you're definitely aiming too low right now.
  5. Which classes, if any, have you been writing proofs in? I would guess that you might have had that in honors linear algebra, and maybe(?) stochastic processes, but I'm a little surprised to not see something like an intro to proofs, advanced calculus, or abstract algebra listed -- not that there's anything wrong with that, of course, I'm just surprised that (say) TAMU's math curriculum wouldn't have you taking one of those by end of your junior year. Then again, I'm not very familiar with your school's curriculum design, so maybe I'm just misunderstanding. I don't know that your research would really be an issue. The ranking of your school in the overall USNews rankings matters, of course, but public vs. private shouldn't really matter beyond that. As a side note, you mean top-50 out of publics, as opposed to a public school in the USNews top-50, correct? Those might help me decide, but bayessays is probably right about your chances, so you should follow their advice.
  6. You should get letter-writers that convince the schools that you are good at high-level math and might be good at research. As important as TA's may be at many universities, you're not going to get into a PhD program because you'd be a good teacher. Even so, with my apologies, I don't think you would get into a statistics PhD program if you applied with your current profile. Your quantitative GRE score is too low, as you know. I'm guessing from your master's program title that it didn't include real analysis, and unless you took that and did very well (in grad school or undergrad), you're gonna have a really tough time getting into a PhD program (and you'd need a 163 or so on the qGRE to go along with it). If you want a PhD in statistics, you'd want to take real analysis and a probability/statistical inference/mathematical statistics sequence and do really well. That might be in a statistics master's, or maybe as postbacc classes, but that would be a start, along with a higher qGRE score and maybe finding some research experience along the way. I'm hardly an expert, so if an older poster contradicts me then you should listen to them, but this is probably a good start. I'm sorry in the present, and I wish you good luck for the future.
  7. Well, let's start with this: if you could get your quantitative GRE score up to 164, I think you'd have a decent chance for most schools except the very top (Stanford, maybe Cal, Harvard, and UChicago?). I might be overstating your chances at each place, but I think you'd have a decent chance to get accepted at UWashington or a school of that level. I can't really judge your research, but you might be in even better shape if it's particularly good work. As a note, you don't really have to submit a Math GRE score except for Stanford, so unless you're particularly interested in going there, you probably don't need to worry about that. With your current GRE score, it is going to hurt a little bit, since sometimes having those high math grades but low quantitative GRE scores makes people wonder about the rigor of the classes/grading scale thereof. At a top-50 school, though, that won't be a big concern -- even less so if your school has a strong math department. As such, it might hurt you a little bit by comparison to other applications, but I feel like some of those schools would still be inclined to "take a chance" (if we can call it that) on someone with your grades. I think that UWashington to Penn State area, maybe down to UCLA or so in the statistics rankings, is a good place to concentrate applications. Overall, I can't really recommend schools for your research interests (although UNC statistics seems a likely candidate), but I think you can apply to more of the elite programs you're interested in. I'm not the expert on profile evaluations or this kind of math, though, so listen preferentially to the more senior posters if they drop by.
  8. Just to clarify my lack of comment: I largely agree with omicrontrabb for statistics PhD programs. I am, however, a little less sure whether all students at unranked/low-ranked biostats programs come in with real analysis (you mentioned an interest in biostatistics research, so I've imputed an interest in biostatistics programs for you in addition to statistics). I also suspect that having a good coding background might in some cases predispose programs to take chances on people with lesser theoretical backgrounds. Even so, you're gonna have a pretty hard time getting into a PhD program without real analysis. At my school, discrete math was very similar to our intro to proofs class, and they could count for each other as prerequisites for math classes; if yours was similar, you might be in a bit better spot that omicrontrabb suggests, but not by a whole lot. Beyond those comments, omicrontrabb's recommendations are worthy of thinking through. Also, I'd imagine Dr. Minin would be happy to advise a former student regarding grad school.
  9. Is there any way you can take real analysis, or otherwise some intro to proofs/sequences and series class this upcoming quarter or two? That would probably do you a lot of good for your viability at many schools. For now I'll defer on giving you a judgment on what schools you'd have a chance at, since I'm not confident in my accuracy, but taking real analysis or a similar class should probably be a top priority if an option for you.
  10. Most people don't have undergrad stat research (particularly methods research, which is the most important kind for applications). The math REU is a definite positive for you. Your research background shouldn't be a problem. Re: letters of recommendation, if the two professors you have close relationships with taught proofs-based math (esp. real analysis/measure theory) or statistical theory, or else were your advisor at your math REU, then you might be better-served by choosing a professor you do know well from a class that isn't strictly math or statistics. I chose a professor from a genetics class because I thought it would tie-in well to how I was selling myself to departments. If you want to talk about being a good statistics communicator, maybe get a professor from a communications/film/theater class that you know pretty well. Maybe you like philosophy of science, and have a relationship with a professor from intro philosophy. Maybe you like genetics or biomarkers or engineering statistics or forensic statistics -- choose accordingly. If those two professors aren't speaking to your ability in math/proofs, though, then my best advice would probably be to talk to them in-person, maybe talk about a class project/time you went to their office, and have your CV, transcript, and at least draft of personal statement/basic angle you're selling yourself through ready to talk to them about. If you got a particularly high grade, that might also be something to note.
  11. I don't know about "most", and these days some schools will partially discourage it by requiring a master's thesis, but it seems fairly common. I'm quite confident that NC State and Duke let people master out, and I know Stanford at least used to. Plenty of others do, I'm sure, but as you might imagine I didn't research it at most places.
  12. Most of what I've heard on hear (I believe at least in part from bayessays, who might weigh in themselves) is that a master's won't really help that much barring special circumstances, e.g. changing fields and taking real analysis for the first time. That is not an issue with you. If you're wary about a PhD, then you are in luck -- UChicago has one of the two best statistics master's degrees in the country (along with Stanford), and unless all of your low grades were in real analysis or something, I don't have any reason why you wouldn't get in. Really, I think you can apply to most of the top PhD programs and work from there. If you don't like or aren't capable of research, then you can choose to master/ABD out, without having to pay back loans from your master's tuition. You'd have to do pretty well on the math GRE for Stanford to accept you, I think, but given that I didn't have a chance at places that highly-ranked, I don't think I can comment very accurately on your chances beyond just that you should do considerably better than I.
  13. You're applying to a slate of schools that seems pretty similar to what I applied to, and I think your profile is stronger than mine, which would suggest that you should probably be able to apply to these schools with a good expectation of some choice (although, as a warning, I do feel like a lot of applicants on here are stronger than I was). Maybe you could aim for a slightly more top-heavy approach to provide more high-tier choices, or at least consider applying to a couple high-ish places in addition to what you already listed above. Bayessays knows more than I do, so I don't intend to disagree particularly, but I think you'd have a decent chance at Duke at least -- since they're pretty exclusively Bayesian, they use a lot of MCMC, and I think that might predispose them to liking people with physics/physics simulation backgrounds. To echo bayessays, the higher ranked biostat departments will have the theoretical background you're looking for. I've usual heard that two of the top biostat programs require measure theory -- Washington (Seattle) and UNC -- so those might be ones to consider as well. That said, they would probably all let you take those more theoretical courses if you wanted, so that shouldn't be a reason to remove Johns Hopkins or anything.
  14. If it eases your feelings a bit, I had a professor who mastered out of a top statistics school and then got admitted for a PhD at another top statistics school immediately thereafter. You would have even less to worry about than they did since you changed fields, and clearly it wasn't a problem.
  15. I'm not very knowledgeable about master's admissions, but I don't think there's really any reason to worry here. You have a 4.0 as a math major, and you took pretty much every class (besides measure theory) that people would be looking for in a PhD applicant(!), plus the GRE scores to go along with it. I'm aware that school "prestige" means rather more than I feel it should in applications (at least for PhD's), but even so, you have the profile of a student who was so good at a less prestigious school that you'd be considered anyways. In any case, master's programs mostly care about ability to do the classes, and you've clearly demonstrated an ability to complete difficult math-based classes well. EDIT: This is to say, I think you can apply pretty much anywhere you want.
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