cyberwulf

Since students are paying, most schools (even elite ones) aren't terribly selective when it comes to admission to their Masters programs. Basically, if the program has a lot of students, the admissions bar probably isn't that high. I'd be surprised if your profile didn't get you into most of the programs you've listed.

What might keep you out of a top 10 program is your relative lack of math courses. Is there a reason you aren't looking at biostat as an alternative? I think your profile would play a little better there.

I would apply this year. I don't think that a couple of co-authored papers (which I assume means you aren't the primary author) are going to substantially change how people view your profile. You have strong math prep from an elite undergraduate institution; I would expect someone with your background to be able to make some kind of contribution on a statistical paper, so the fact that you have doesn't convey much beyond what is already in your application. As you note, a minor weakness of your application is your math grades, but grades are mainly a predictor of whether or not you can handle the coursework, and speak to a different dimension of your profile than research potential. Also, I wouldn't worry too much about the lower verbal score; it's adequate, and unless you think you can score a 166+ I don't think retaking the GRE is a good use of your time.

I have a hunch that you're the kind of applicant that programs may want to "take a gamble" on despite your relatively light formal math background. Things working most strongly in your favor include strong performance at an elite undergraduate institution and extremely impressive GRE scores. Also, through your physics courses you've likely been exposed to many more mathematical concepts and techniques than is suggested by your relatively short list of "named" math courses. I don't think your list of PhD programs is at all unreasonable; I wouldn't be surprised if you got into a couple of pretty highly-ranked programs.

If you actually have meaningful research experience in a particular area (or areas), then it makes sense to target schools that specialize in those areas. Otherwise, I wouldn't spend too much time worrying about it.

There's really no reason not to submit extra letters unless a school explicitly says that they will not accept them. I'd guesstimate that about 5-10% of applicants to our program submit more than the required 3; usually, it has relatively little impact on their admissions results.

I think you should strive to have at least 2 letters from people with PhDs.

I don't think there's any way to avoid the awkwardness of sticking around in a program after it becomes known that you've tried to leave. I would recommend that you only apply to transfer if you are committed to leaving your current program, which may even entail a step down in prestige level to find a program which is a better fit for you.

Being able to write "proficient in R" (or Stata, SAS, etc.) somewhere on your resume will have virtually no impact on your chances of graduate school admission. The reason to learn R (or another language) is to better prepare yourself for graduate coursework or the post-graduation job market. R will definitely be the best prep for graduate work, as virtually all academic departments operate mostly in R. For some industries (like pharma), proficiency in SAS remains a marketable skill.

University of Washington Statistics is home to CSSS (https://www.csss.washington.edu/) and offers a Masters degree with a Social Science track. At the very least, it's a starting point where you might be able to identify some keywords to search for other similar programs. Alternatively, you might look into sociology programs, some of which are quite quantitative.

That's a reasonable list on the Biostat side, given your profile.

Given your geographical preferences, your obvious choice is University of Chicago. It is head and shoulders above both of the other Chicago options. Given your profile, it seems like you stand a pretty decent chance of getting in. Honestly, there aren't a lot of schools that are clearly better and you should consider leaving for; maybe Stanford and Berkeley?

While transferring out of a top-level program isn't common, I don't see any reason why top stat programs wouldn't give your application serious consideration. This is one of the rare circumstances that the statement of purpose is really important; you want to be very clear about why you are transferring (and it sounds like you have good reasons to write about). Also, I would strongly recommend that you get at least one letter writer from your current program, and ask them to mention that you are leaving while "in good standing"; i.e., you aren't abandoning ship because you failed a qualifying exam, were caught plagiarizing a paper, etc. Basically, you want your advisor to say that they're really disappointed to see you go because you had a lot of potential.

I wouldn't be surprised if you got into all of the programs you listed.

Yeah, that seems like a fairly reasonable list. I would imagine your chances of admission are pretty good at UConn and BU, and you would likely be "in the discussion" at NCSU, Columbia, UNC, and UCLA. Duke seems like a pretty tough nut to crack, but with really good letters, it's worth a shot. Northwestern is very a small program with an admit rate much lower than its stat department's reputation would dictate, so it's hard to figure your chances there.

Don't bother. You got a bunch of A's in advanced math classes at a Top 10 institution; what would taking the math GRE prove that your transcript doesn't?

I'd posit that you want to learn applied statistics from faculty that 1) have deep insight about and understanding of statistics, and 2) are doing important, high-profile work in applied statistics. Such faculty are likely to be strong researchers, and hence working at departments that are highly-ranked.

You won't be able to get any meaningful research experience in a few months, so I would suggest taking more advanced mathematical coursework. Your "in" to a good program will be preparation, i.e., that you have a more extensive mathematical background than many applicants. You are hoping that schools will therefore view you as a "safer" bet to succeed in the coursework than others with less preparation.

I think that Q score's "good enough" that, combined with your excellent grades in a large number of math courses, it won't hurt you that much. I don't think it's worth changing your original list of schools dramatically.

Not much to say, really. You're a strong candidate, so you should apply to all the good places in the places you'd like to live. Stanford is a tough nut to crack for Canadians, but seems like a logical addition to your list (though you might have to take the Math GRE, which is a pain).

I didn't mean to imply that it was trivial for anyone to figure out which schools fall in which category; rather, I was pointing out that it was possible to reliably rate an applicant's chances in this way using a relatively small amount of objective data that didn't include squishier things like "research interests" and "availability of a suitable advisor".

This might be true in the social sciences, but it's not how things work in fields like stat and biostat, where students are admitted chiefly on the basis of their academic record and research potential and only identify research interests and advisors once they've been in the program for a couple of years. Given a student's profile (even just basic school/GPA/GRE information), in our field(s) it's usually pretty easy to figure which programs are reaches, which are decent shots, and which are quite likely to admit them.

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.

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.

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.