cyberwulf

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.

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.

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.

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.

This varies a lot; an incoming class could be anywhere from 90+% PhD students to 50+% Masters students.

First, you go past the big fountain... then you cross the red square... and that's how you get to STAT 512!

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.

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.

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.

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.

U of T stat is a pretty decent department, but biostat is pretty much unknown.

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.

Agree.

Your list is fine.

Don't get me wrong, I think the overall profile is strong. However, there are a couple of lower math grades (e.g., C+ in Calc 3), and the overall GPA suggests a couple of lower grades in other courses as well. In addition to the strength of the letters, a lot of @mcaleste's success will depend on the strength and reputation of the "large state school" he attends. If it is a major state flagship (like, say, University of Virginia or similar), then this profile may be enough to get him into a top-tier program. Otherwise, probably not.

Yeah, I think you're going to have a tough time getting into a lot of the schools on your list. When you combine your relative lack of mathematical preparation (e.g., no real analysis) with the fact that Kansas State doesn't have a particularly strong student body (about.com says 95% of applicants are accepted there), there are going to be some legitimate doubts about your ability to do the math required in a good Stat PhD program. If it's feasible for you, you might want to consider starting in a good Masters program to get some more advanced coursework under your belt, then use that as a stepping stone to the PhD.

Yes. Research experience is becoming a bit more common as stat/biostat filters down to the undergraduate level, but admissions continue to be driven largely by the three core components: grades, letters, and test scores.

Typically, funded MS offers are reserved for students that a program would very much like to "have around" as a potential future PhD student, but either didn't have the necessary quantitative preparation or didn't quite make the cut for PhD admission.

That is a reasonable list, but I'm not sure why you're classifying UNC and Michigan as reaches but not, say, Emory. UNC and Michigan are very large programs which accept a lot of applicants, while Emory is much smaller and therefore often has a higher bar for admission. Of course, that's not to say that Emory is a better program than UNC and Michigan, but rather to point out that difficulty of being admitted doesn't track exactly with school rankings. I think that places like UNC and Michigan are very reasonable targets for someone with a profile like yours. Michigan might be particularly appealing to you because of their strength in statistical genetics.

@yohesh92 You should be aware that some schools require a minimum TOEFL score of 100 to consider you for admission. How strictly this policy is enforced varies between programs.

If your grades are solid (say, equivalent to a 3.5 GPA) and your undergraduate institution has a decent reputation (i.e., a faculty member from your country working at a U.S. institution would know of it) then you are not wasting your time. Your math background is more than sufficient for Masters admission.

The risk you run of making a big deal of your interest in TDA in a personal statement submitted to a biostat department is that people could say "we have no one here doing that, so I doubt he's really interested in coming here." Or worse, "this guy has no idea what type of research people in biostat do!" So, nothing wrong with mentioning TDA as something you've done work on and are interested in, but unless you can explicitly link it biomedical applications, for biostat programs I'd lean more towards the functional data and Bayesian stuff.

I don't think it's implausible that you could be admitted to a couple of schools on your list (I would think chances are better at Wisconsin/Columbia/UCLA than CMU/Duke/UW), but I would recommend adding some more places ranked in the 15-25 range as safeties.

A 167 will help you, but not at most/all of the schools you listed. The average entering undergraduate GPA for students at UW, UNC, Hopkins, etc. is around 3.9, and having Masters degrees (with what is, frankly, fairly average performance given the grading scale in graduate school) will not help you that much. You're also facing the challenge of being an international student, so the bar is even higher than what the overall student profile at these schools indicates.

Realistically, I think you will struggle to get admitted to any U.S. Biostatistics PhD program ranked in the top 20. I would not recommend you spending your $$$ applying to Washington, Hopkins, UNC, or Berkeley; they all routinely reject applicants with records much stronger than yours. UCLA and UC Davis are somewhat less competitive, but not by much. I don't want to be too negative, but the fact that you got a 148 Q score on the GRE after having done the volume of quantitative coursework that you have will be a major red flag unless you can dramatically elevate your score on the retake. It's hard to know what programs to suggest, because I'm not very familiar with the admissions practices of low-ranked (or unranked) biostatistics programs, but I think those are the ones you'll have to target if you're set on doing a PhD.