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About health_quant

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    2013 Fall
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  1. If you're interested in enrolling in a doctoral program after the MS, one big benefit of attending Brown's program is its small size. With fewer than 10 students entering each year (~3 being doctoral students), it may be easier for you to establish closer relationships with the faculty there. Letters of recommendation will be extremely important for further graduate study, and solid references may help to obtain a position in industry (though I don't know how common it is for employers to check recommendations for MS-level positions).
  2. I think you and I are in similar boats this year, and maybe even the exact same boat. (I am assuming that by second-tier stats program, you are still referring to a top 10 or top 15 stats program, as tiers on gradcafe seem to be used to distinguish between programs within that upper echelon.) I think that what earlier posters have noted about academic job placements (i.e., publications outweighing school names) really is the most important factor to consider if you want to go the academic route yourself down the road. The top biostats programs seem to do consistently well in preparing th
  3. I'll echo Kimolas and recommend getting more research experience (and checking with your undergrad professors is a great idea). Your math background is far from weak, so I don't think that taking the math GRE will give admissions committees much more information on you as an applicant. For what it's worth, a friend of mine was admitted to Washington's PhD program in statistics without an undergrad major in math or stats. He did, however, have a lot of relevant research experience.
  4. I would agree with you regarding Stanford and CMU, but UW versus Cornell, Michigan, or Wharton is definitely debatable (especially the latter). Among the new and/or incoming ML-related hires at UW: Carlos Guestrin (formerly a prof at CMU in ML/CS); Emily Fox (formerly a prof at Wharton); Ben Taskar (CS/Stats at Penn Engineering/Wharton). There's definitely a big push from UW to build up ML in the stats department (while integrating with UW CSE), while biostats and stats have historically been linked quite closely.
  5. Uromastyx is right on. For the school, extending an offer to someone who isn't completely committed to their program could tie up one of their admissions slots for weeks and delay them from extending the offer to someone on their waitlist. Just like we'd like to hear back from schools as soon as possible, schools want us to decide quickly, so that their own waitlist doesn't evaporate while those waitlisted students take other offers. If this is your top choice, let them know. It seems likely that they want to admit you, but they just want some assurance that they're not wasting their time.
  6. I don't know for certain, but if they're doing more rounds of reviews, then it seems their offers wouldn't be limited to people who attended that day. Given the strength of their program, I imagine that Brown's yield is good, but it's still possible that they could exhaust their initial list of interviewees without filling every slot, as those initial people are probably receiving multiple competitive offers. I think that at this point, we should consider no news to be good news (which also applies to any other schools from whom we haven't heard).
  7. Brown's biostats program is very careful with its admissions process, as they only aim to admit 3 or so doctoral students per year. During the (first? only?) interview/recruitment weekend this year, there were only about 8 applicants present per arm of their public health program (biostats, epi, health services research). Despite being relatively small, the biostats department is doing some extremely interesting work. They're definitely among the top picks of the schools to which I applied. Fingers crossed that we all hear some good news soon.
  8. As others have pointed out, all of the aforementioned are top-notch programs, but it seems that even within this upper echelon of schools, distinctions are still commonly drawn. When we're looking at the total population of schools, I agree that these are nearly all top-tier programs. As far as this thread goes, the distinctions seem to boil down to drawing sub-tiers within that topmost tier.
  9. Same here. I'm scratching my head because I've gottten responses from Washington (biostats) and Wisconsin (stats), both with full funding, but not a peep from UNC. I thought the concordance of admissions from these places would be pretty high...
  10. The level of theory seems to vary quite a bit across Biostats departments. For Michigan, the Biostats doctoral students take the same requisite graduate, upper-division sequence in mathematical statistics as Stats doctoral students, but are not required to take the measure-theoretic course in probability. Perhaps it's also worth noting that Michigan's more measure-theoretic coursework is cross-listed in the Math department. Similarly, Penn's measure-theoretic probability sequence (with stochastic processes) is cross-listed under the Math dept. The doctoral-level stats c
  11. haha. so true. spending all our time on thegradcafe doesn't help with maintaining a broader perspective...
  12. Their placements in biostats departments are quite good (high numbers of graduates in well-ranked programs), but I know less about their placements in stats departments.
  13. This is definitely going to be a tough decision, so don't feel pressured into rushing it. Whether you decide to attend Berkeley or Minnesota, you'll be in a very good position down the road. Some points in favor of Minnesota (as my last post was kinda pro-Berkeley): As others have already pointed out, Minnesota is a top-notch program, and at least in biostats, comparable to (if not outright stronger than) Berkeley. If you're planning on going into a non-academic (or even non-statistical) career, the Berkeley name may count for more, but within biostats, people will know what
  14. I think Berkeley is still worth serious consideration. Being a funded MS student at a relatively small department should afford you a number of good research opportunities with well-respected faculty in biostats (and possibly stats). Assuming that you make a good impression there, you would be extremely competitive for doctoral programs at the top schools (Hopkins, Harvard, UW Seattle), and you would presumably still be at least as competitive for Minnesota then as you are now. I may be biased though, as I'm currently a funded MS student (at a comparable biostats program to Berkele
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