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bayessays last won the day on June 29

bayessays had the most liked content!

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About bayessays

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    2020 Fall

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  1. I saw someone with a JASA paper from their master's who didn't get into any top 30 programs. It's still rare. Stanford statistics is really in a league of its own, so it's not surprising to me what an international student their had an Annals paper, but to be fair, cyberwulf did say "from this cycle" and this guy is a year into his PhD and the paper has still only been accepted and not published.
  2. Could definitely apply to any. In CS, you apply to a lab. In statistics/biostat, you apply to department and choose an advisor after a year or two. Most statistics applicants don't have much statistics research experience at all. No problem at all. Doesn't matter, do what is most interesting to you so you can do well and get a good letter. I think you can pretty much apply anywhere for stat/biostat. Pretty sure you'll get into top 5 biostat programs and top 20 stat programs. Don't just apply to the top 5 schools. UW, Berkeley, Chicago are probably achievable but you can't guarantee with schools at that level. MIT/Stanford are probably reaches. Schools like CMU, Duke, Michigan, and the top 3 biostat programs are probably good targets with a couple reaches and couple lower ranked programs.
  3. I think you'll have pretty good results. I've seen some people accepted to PhD programs with sub 160 scores. Your math grades are all As, you have some relevant research experience - my guess is you'll get into over half these programs if you applied with current stats.
  4. Your math background is fine for stats programs. UCLA's statistics program is more prestigious than their biostat program, so admissions will probably be harder though.
  5. Probability, mathematical statistics, real analysis, linear algebra. If you've taken all these, take numerical analysis and a class where you'll learn R. Other higher level math classes like algebra will help show math readiness but won't be directly applicable. Undergraduate applied statistics courses aren't going to help much.
  6. Not a big deal. I think the difference will be small enough where you should take what you want. Probability is obviously more important in general though, but since you have a probability class, this choice matters less. Your math background is strong, and your research experience is definitely above average. I think you have a good shot at getting into a few of these programs - I would be especially surprised if you didn't get into TAMU so I don't think you necessarily need to have any safeties. I would look at FSU and UCSC as schools that are safer and also fit your research interests (UCSC is strong Bayesian focused program). Also definitely look at UC Irvine. You can do the correct research and everything in a Biostatistics department, but the environment is different and you'll likely get less teaching experience depending on department (it's in a school of public health, so there are often no undergrads to teach).
  7. U Florida, U South Carolina, Medical U of SC. To be clear, definitely still apply to Vanderbilt, I just think it is not a certainty but it is a totally reasonable school to apply to with your profile.
  8. I think Vanderbilt is going to be somewhat of a reach for the PhD. They seem to be a pretty competitive program for their rank for a variety of reasons. Is it feasible for you to take some more math (like real analysis and probability/math stats)? If you could do that I think you'd be much more competitive. I don't think you need a master's if you can take some more math now. I think you are selling yourself short if you go to unranked programs like Tennessee or Mississippi.
  9. Your assumption about biostatistics departments is generally not correct - admissions are generally handled at the department level. Chicago statistics is the only school I know that explicitly mentions your profile will be reviewed by professors with similar research interests. I don't think this situation you're imaging exists, because the problem of having a bunch of good candidates who are hard to distinguish is not true. Even if there are 100 domestic applicants with high GPAs and perfect GREs, then you group them by the prestige of their undergrad, their research experiences, their letters -- there are decisions to be made on the boundary, but if I showed you the profiles of Stanford and CMU's new class or Washington biostat vs Michigan biostat, you could probably guess which is which -- not everyone at a top 10 program is a genius, so there is lots of variation even at the top. Secondly, there is no true ranking. Some programs have different goals, cultures, and want to accept different types of applicants. A ranking of applicants would need a define criteria (eg "most successful academic career ahead"), and those are different for different departments. "will succeed in completing a PhD" is probably the most important criteria, and that would only produce a categorization, not a ranking. But these are just irrational humans reading a set of documents and choosing which other humans they want to offer to come to school. I don't see what you gain from conceptualizing a "true ranking" -- you have to be clear about what this means or measures or the idea is meaningless. "Quantifying people as just a number" isn't just a moral issue because it could be dehumanizing or because it's hard to estimate -- these numbers literally do not exist in any meaningful way. Most importantly, this is not how admissions works, so even if the applicants are hard to distinguish in this ranking system, the school doesn't need to stress too much about ranking the top 20, because of self-assortment you can send 30 offers, 30 waitlists, and let the students self-assort. Why stress differentiating between applicants 3 and 4 if they're both going to go to a different school? Edit: To be clear, I enjoyed thinking about this and it brings up interesting issues/gets the wheels churning about how to think of the problem in a statistical way, but I just don't think it has much basis in the real world.
  10. Is there a particular reason your second choice is the applied math program? If being in Seattle is important and you want to study statistics, apply to both the statistics and Biostatistics departments.
  11. My guess is you would be competitive. It seems like a pretty applied program (they don't require or even recommend analysis, for instance), so I imagine the solid math background and MS will make you competitive even if your grades are a little low.
  12. I didn't know they had a program either. I cannot speak to whether their graduates are able to get good jobs doing applied statistics, but this is not a top 20 biostatistics program. The program barely has any math requirements for admission and I don't see any methodological research going on.
  13. I don't think you have to go lower than that besides for a safety, I think those schools are in the range you should target. There's a lot of other good programs in the Midwest too that are similar - Ohio State, Wisconsin, Illinois, Iowa State, Northwestern all have people in areas you are interested in. I don't think you should be concerned about your math background at all. Some safer Midwest schools for you would be Iowa Biostat, MSU, Indiana, Notre Dame.
  14. If you are taking the classes in the fall, you can send in your updated grades. Then I don't think you'd need to wait a year. But since you have such a good GPA, I think you will get much better results having some more math on your transcript.
  15. First, the GRE is out of 170, and is an important part of the application, so it's hard to give exact recommendations without that. But your currently thin math background is the bigger concern. I think you'll need some of those real analysis/probability/math stats classes on your transcript to get into a top 40 program. I don't think these schools are going to be realistic right now. If you get As in real analysis and your math stats sequence and a good GRE, schools like UCLA might be reachable. What are your interests? Statistics PhDs are very theoretical, so if you haven't taken any math beyond linear algebra or a mathematical statistics course, it's hard to get a picture of what you would like to do. Have you looked into biostatistics programs? They are generally more applied, especially outside the top 5 or 10.
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