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cyberwulf

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cyberwulf last won the day on November 18 2016

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About cyberwulf

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    Biostatistics (faculty)

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  1. There are two main reasons that it is harder to be admitted to stat and biostat programs as an international student: 1) Funding for international students is (somewhat) more limited. NIH and NSF grants are only available to U.S. citizens and permanent residents, so a department is more likely to have to "pay in full" to support an international PhD student. I've heard people on this board mention that international students are "more expensive" because their tuition is higher, but many graduate schools either a. charge the same rate across all students or b. have things arranged so that students with RA/TA support (i.e., all PhD students) all cost the same amount. In any case, I've never heard a faculty member at another institution mention tuition differential as a reason for not accepting more international students. 2) Students for whom English is not their native language face the double challenge of learning the technical material and learning to communicate (write, give presentations) in English. Since a lot of research and collaboration is about communication, the path to academic success is objectively more difficult for non-native English speakers. Since it is difficult to precisely quantify the English proficiency of most international applicants (the TOEFL is a lot like the GRE Q; if you score too low, that's a bad sign, but above a certain level there isn't a whole lot of information), admissions committees are basically hoping that by raising the bar high enough, they will admit international students so talented that their raw ability will allow them to overcome any communication difficulties. @biostatboi: As a Canadian, you're subject to #1 but not #2. So, Canadians (and Australians, Brits, etc., but they rarely apply) occupy this sort of halfway point between U.S. and international applicants. My guess is that aggregated admissions data would bear this out; it is somewhat harder for a Canadian to gain admission than an American, but easier for a Canadian than someone from China or India. Bottom line: Your profile is quite strong; you should apply to good places (your list seems pretty reasonable), and I think you'll get into a few.
  2. I'd say that not much has changed, reputation-wise, in the past five years. Brown is still a very good (though very small) program, which probably ranks around #10.
  3. The math GRE is most likely to benefit a student with an otherwise excellent record but who has taken relatively little math (for a top program, say "only" up to undergraduate real analysis and abstract algebra). Then, a good score in the math GRE (which I would qualify as about 75-80th percentile) would be helpful. Another student profile that could benefit is someone who has a very good but not outstanding record in math classes, but absolutely crushes the math GRE (say 90-95th percentile). In both cases, the math GRE score adds useful additional information to the profile which could elevate them enough get into a place they might otherwise not.
  4. This just isn't done in the field, since you are (typically) being admitted to a department and not to work in an individual faculty member's "lab". You didn't miss out on anything by not doing it.
  5. Yes, this. Indeed, the top departments tend to be the most "hands off" because they have (on average) stronger students who can work quasi-independently. As you move down in the ranks, faculty often play a bigger and bigger role in driving student research and publications.
  6. Most places that do interviews have already ranked the candidates before the interview. A great interview might bump you up a few spots, a not-so-great one might move you down a bit, but in most cases your rank probably won't change much. It's possible that you were just outside the admissions line even before you visited, and your interview wasn't "great'' enough to change that.
  7. Interesting discussion. A couple of thoughts: 1) It's very hard to judge placement records on the basis of a few years of data, because the sample sizes are relatively small and 2-3 strong students can make it seem like a program is doing great over a short timespan. Complicating matters is the fact that, starting about five years ago, there was a massive shift in hiring practices such that it has become uncommon for students to land jobs at top 10-15 departments without first completing a postdoc. 2) That being said, I just don't see the evidence that Michigan has had great placements in recent years. They are almost certainly outpaced by Hopkins, and likely UW and Harvard as well. Berkeley and Minnesota have also had some notable successes. 3) biostat_prof doesn't seem to drop in on these boards much anymore, so it's a bit unfair to take shots at her/him, but they are clearly a UNC "homer". I have also been involved in admissions at a good program and it is objectively false that the incoming class at places like UNC/Michigan/Minnesota/Berkeley is on par (in terms of pedigree, preparation, etc.) with those at the "top 3". Some schools do a better job than others at maximizing the talent they get, but there is clearly a talent gradient as you move down the rankings.
  8. This varies a lot; an incoming class could be anywhere from 90+% PhD students to 50+% Masters students.
  9. First, you go past the big fountain... then you cross the red square... and that's how you get to STAT 512!
  10. This certainly isn't a useless metric, but the number of ENAR award winners from an institution is closely tied to the number of submissions from that institution, which in turn is a function of the culture/expectations about submitting to student paper competitions at that institution. It simply strains belief that, if the number of submissions were similar, Harvard and Hopkins wouldn't rack up at least as many awards as UNC.
  11. Berkeley has had much better academic placements than Columbia in the past 10 years: Kasper Hansen (Hopkins), Sherri Rose (Harvard), Maya Petersen (Berkeley), and Alex Luedtke (Fred Hutch/UW), among others. I can't think of anyone going to a top-tier biostat place recently coming out of Columbia biostat.
  12. An easy way to figure out the typical PhD cohort size is to count the total number of students in the program (usually available on the department's website) and divide by 5. Not perfect, but it'll get you in the yard.
  13. Wisconsin is the only well-established program on this list. The program is shared with stat, which has produced many excellent graduates. Of the rest, Florida and South Carolina (I assume you mean Medical University of South Carolina) are "OK", and the remainder are pretty much unknown and have almost no track record of sending graduates into good postdocs leading to faculty positions.
  14. U of T stat is a pretty decent department, but biostat is pretty much unknown.
  15. From a faculty perspective, SIBS is certainly a "thing to do" but typically doesn't provide much useful prep for grad school in biostatistics. It is most useful for those who have no idea what biostatistics is and want an introduction to the field. If you are already sold on biostatistics, SIBS likely won't boost your application that much since: 1) a lot of applicants do SIBS, so it's not a differentiator, and 2) because the programs are so large (20+ students), letters from SIBS advisors/mentors are typically pretty generic. Honestly, I think a potential biostat applicant's time would be much better spent doing a research project (or smaller REU) over the summer.