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floffel

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  1. I'm not sure it's worth taking grad level measure theory/probability if you are already planning on going to grad school in Statistics. Most PhD programs assume you will take this material your first year, and even if you take it now you'll probably want to take it again to make sure the material is very fresh when you take quals, and because classes like that are pretty foundational for most programs. More math is never a bad thing, even if the areas aren't that relevant to Statistics. I'm assuming you've done real analysis and linear algebra. Functional analysis, fourier analysis, and complex analysis would all also be useful courses for Statistics. Also, definitely take some Statistics classes (probability doesn't count). I think it's important to show a genuine interest in Statistics rather that just one-dimensional mathematical aptitude. For research, working with a statistician would be best, but either of the other options you mentioned would certainly still be valuable. Research experience is definitely an important part of the picture. Lastly, like anything else GPA of course matters, but how much depends on the quality of your undergrad program, letters of recommendation, research, etc. Good grades are obviously desirable, but average grades can be made up for by great letters, experience, and enthusiasm.
  2. The site phds.org lets you rank programs based on newly available data provided by the NAS/NRC/etc. It's a long-awaited update to the original 1993 edition.
  3. Stats PhDs are indeed very marketable. If you invest the time and money now into getting a PhD, you can easily get 6 figures and maybe end up running an actuarial firm yourself later down the road. Also consider that, generally speaking, the longer you wait after undergrad to begin grad school, the harder it will be to get in to your target programs. On the flip side, if you go to graduate school now and ultimately decide you'd like to go into industry, simply leave after a master's... which will get you significantly better placement anyway. I don't know much about the actuarial exams, but if you like taking difficult tests there's always the GRE math subject test. =P
  4. I wouldn't worry about what department your recommendors come from so long as they speak about qualities important to being a statistician: mathematical aptitude, computing experience, data analysis, etc. I have spent the past year working for an economist (I'm starting stats phd this fall) and had 1 letter from math, 1 from stat, and 1 from econ. Obviously, stat departments won't know mathematicians and economists as well as they'd know other statisticians, but statistics is a small enough field that I don't think any grad programs expect undergraduates to have encountered three statisticians who can write letters for them. Also, since statisticians do a good deal of research in collaboration with people in other fields, having diverse recommendors shows your potential to be a valuable member of the scientific community as a whole. What does worry me a bit about your profile is that you don't seem to have done that much statistics. It's pretty common for incoming stats grad students to have only a few stats classes during their undergraduate curriculum (most schools don't have a stats major), but one class is simply not enough. You also don't mention a BA or research done in economics, or any work experience that has you analyzing real data sets. I think that PhD programs will be unsure of how much interest you really have in the field given a relatively thin exposure to it. That said, your grades from a well-respected school clearly show you have a lot of intellectual potential and I think, assuming strong recommendations/personal statement, you would definitely get into top 20 masters programs and be competitive for top 10. Doing a masters would also obviously beef up your stats creds for applying to PhD programs and signal your commitment to the field and academia in general (I think applying for a masters before PhD makes a lot of sense for people who have been outside academia for a few years). There are indeed some masters programs that have funding. The reason is that lots of schools have massive undergraduate intro stats classes and are in constant need of TAs, so they use both masters and phd students. Though I don't know of a way to find a list of all schools that do this, big public schools are a good bet. Wisconsin, Washington, Michigan, A&M, NCSU, UNC, are all very good statistics programs and might have funding for masters students (there are others I could have added that list).
  5. Apples, Your profile seems like it meets all the basic requirements to be a competitive applicant. The GRE general isn't really all that important as nearly everyone has an 800 or 790 on the math portion and I doubt the verbal portion matters much. Most applicants are math majors who have taken some stats (data analysis/probability/math stat) and programming, and have good GPAs. Standing out from the pack is really going to come down to your letters and the specific nature of the math and stats programs at your school (is your school well respected in math/technical fields as well as overall?). Even though you're interested in applied stats, you need to have a good theoretical background and this includes math stats (be sure to take this course and do well in it). I also wouldn't totally dismiss the personal statement. Though it won't compensate for weak technical qualifications, it's an important part of helping departments see how well you'll 'fit'. Statisticians enjoy the versatility and interdisciplinary nature of the field, and it is important to show that you want to be a valuable member of the scientific community as a whole rather than somebody who simply like calculating odds and running regressions. As for the GRE math subject test, if you can do well on it without spending months studying for it, go ahead and take it... a good score definitely can't hurt. Otherwise don't bother, as only a few schools require it and the time you'll need to study for it is probably better spent on other projects.
  6. How strong are the programs you've already completed? Unless you are coming from a very rigorous program, your undergrad GPA is quite low and this could be a problem. Also, most of the incoming students at the schools you were targeting will not have a master's in math (much less two). I'm not sure whether this is because top programs dislike taking people with a master's or simply because most good math students (ie, the people you will be competing against to get into those programs) go straight to PhD programs. If you are foreign having the master's is more normal. The most important factor in your application is your recommendations, so while it's hard to know what programs you can get into without knowing your LORs, your recommenders will likely be able to help you calibrate your list of schools--ask their advice.
  7. You need to aggressively get in contact with the department ASAP (call, do not email). Try contacting professors instead of/in addition to admins. You need to have specific reasons why you really want to go to Stanford and a good explanation for why you were uncommunicative/late in responding to their offer. You can't just sit back and hope everything works out; you need to take an active role in negotiating this program and anything else you may still have on the table. Is the position funded? If not I imagine it will be easier for them to take you.
  8. It seems to me this is as good as any list is going to be. Of course there are slots that seem a bit puzzling, and depending on someone's specific interests the list could look very different. But every program on that list is a good program, and I can't off the top of my head think of a great program that does not show up there. One thing that's for sure is that UW's funding problems for Stat for this coming year is going to hurt them in the next edition of these rankings. It's such a shame considering how great that department is.
  9. Wisconsin has better theoretical training and has a great placement rate. It is also definitely the right choice if you are interested in biostatistics. Michigan is a great university and Ann Arbor is a fun place to be, but Wisconsin is definitely a better choice academically (Madison is fun too, by the way).
  10. I had a similar experience with contradictory ratings. Reviewer 1 said "broader impact is completely missing from the Proposed Plan of Research document. It is hinted-at in the Personal Statement but could be elaborated to a much greater extent," while reviewer 2 said "You are clearly someone who has broader impacts in mind and will seek them out". Overall I got Poor/Fair from reviewer 1 and Good/Good from reviewer 2, neither of them offering particularly helpful criticism. I am also confused as to whether the ratings refer to the only the essays or the entire application. I don't mean to sound cocky, but it's hard to imagine being rated "Poor" regarding intellectual merits when I double-majored from an elite school with a high GPA and nearly perfect GREs. Are these sort of things valued at all? And where do LORs even come in? I wasn't necessarily expecting to get the award in the first place, but it's a bit depressing to see that it looks like I didn't even come close. I spent a lot of time on this application and showed it to several professors who thought the essays were excellent. I suppose I'll reapply next year, but I honestly don't see how I'm going to have an application that's dramatically better than this one. From what I've seen here regarding the variation across ratings and priorities, maybe I'll just have to hope for the right duo of readers.
  11. The only program of those that I am familiar with is Statistics at Chicago. While that is a great department, it might not be a great fit for someone who is also considering Operations Research/Industrial Engineering. The U of C Stat department is among the more theory-focused of the top Stat programs, and the research applications tend to focus on the social sciences (primarily econ), business, and genetics of course. The University as a whole does not have many people in Applied Math, and though I can't speak for IE specifically there is virtually zero interest in Engineering throughout the institution.
  12. The only program of those that I am familiar with is Statistics at Chicago. While that is a great department, it might not be a great fit for someone who is also considering Operations Research/Industrial Engineering. The U of C Stat department is among the more theory-focused of the top Stat programs, and the research applications tend to focus on the social sciences (primarily econ), business, and genetics of course. The University as a whole does not have many people in Applied Math, and though I can't speak for IE specifically there is virtually zero interest in Engineering throughout the institution.
  13. You are in a very enviable position to be choosing between such great programs. I think most of the statements you make about each program are accurate, except perhaps the importance you attach to the Harvard name. Firstly, the University of Chicago has an outstanding reputation as an institution overall and shouldn't really be seen as less 'prestigious' than Harvard. It's true that to the outside world the name 'Harvard' stands out quite a bit, but within academia and the business world the U of C is always mentioned in the same breath as Harvard, MIT, Berkeley, Stanford, etc. when considering the quality of research and instruction. Secondly (and you probably know this), the name shouldn't really be an important factor after all...
  14. Assuming you go to a school with a reasonably good reputation, you could probably get into top 20 programs with what you have already. Taking some more math and a programming course or two will give you a decent shot at some top 10 programs IMO (again, this is assuming you're in a decent program already).
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