cyberwulf

The point of a lot of my previous posts is that it's a combination of factors which make a successful applicant. There are very few "perfect" applicants, so we end up balancing each applicant's strengths and weaknesses. Great letters can make up for a lower GPA (within reason), mediocre test scores might give some people pause even if grades and letters are strong, lots of good grades in rigorous math courses can sometimes overcome unexciting letters, etc. No one factor dominates.

The conclusion from the above is obvious: reporting your GPA on GradCafe increases your chances of being accepted!

One thing to keep in mind when looking at these data is that the GC population is a highly biased sample of applicants. For instance, it is much more heavily domestic (i.e., U.S.-based) than the overall group applying to stat & biostat programs. This is one of the reasons (among many) why you're seeing admit rates in the 40-50% range from the results page, while most top programs report rates under 20%.

Just FYI, the 'Statistics and Probability' rankings are missing basically all of the top biostat programs. They are listed under 'Public Health'.

I suspect the 150 number from last year may have been PhD only, and the 300+ they're quoting for 2014 includes MS applicants as well. But there's no question that applications are way, way up across the board, maybe as much as 20-30% over last year alone.

Feel free to PM me about this if you want.

There are "obvious admits" at every level of school, even top-tier places; as evidence, if you surveyed junior faculty at top programs, you would likely find that most "ran the table" (or came close) when they applied. Also, it is possible to draw distinctions between even excellent applicants, although you could make the argument that such distinctions are of little practical significance. In your hypothetical example, there are several dimensions on which those two applicants could be compared: individual course grades, letters of recommendation, GRE scores, previous research experience, etc. It's unlikely that they will be identical in all respects.

Gauging the applicant pool is tough for us from year to year as well, especially recently as stat/biostat have become higher-profile disciplines and attract more applicants. The best thing you can do to figure out the expected level of competition is look at incoming class summary statistics (where reported) and do a little "CV snooping" on current graduate students who have web pages. Mediocre/lukewarm reference letters can be a problem, particularly if you are part of the "in the yard" group being discussed for admission. Unfortunately, "praise inflation" is rampant in academia and very positive letters are the norm, so something less than that may hurt your chances. Of course, *one* less-than-stellar letter can be dismissed as an outlier (or the rare professor who writes more honestly), but if faint praise becomes a pattern across multiple letters, that's more of an issue. Also, on a related note, people worry WAY too much about the "name" of the person writing them a letter. The vast majority of applicants have all their letters from people whose names we don't recognize, and it doesn't hurt them one bit. Sure, a handful of students have letters from "famous" statisticians, but that only confers an advantage if the letter is fairly strong. It's much better to have enthusiastic letters from "no-name" professors who know you well than a so-so letter from an eminent statistician.

To answer some of your questions, here's how we do things in my department. I would expect that things are not too different elsewhere: - The admissions committee is composed of about 5 faculty. - All members read each PhD application; there is no "pre-filtering", though it's unlikely your application will be read in great detail if your "top-line" numbers (GPA, GRE, TOEFL for international students) are way out of line with department norms. We receive translations of international transcripts, and can usually get a decent handle on how good these students are. - Some number of applicants are "obvious admits", their profiles being simply outstanding in all or most respects. Usually these "slam dunks" occupy about 20-40% of the offered spots. The "good" and "very good" applicants compete for the remaining spots. - After scoring the applicants, the committee meets to focus on the applicants who are "in the discussion" for PhD admission. Factors working in favor of (e.g., really positive letters) and against (e.g., lower grade in an advanced math class) each applicant are discussed and weighed. Sometimes, a faculty member will "go to bat" for a student they think highly of, even if that student ranked a bit lower in the initial scoring. - As I've noted before, applicants worry way too much about research experience and the personal statement. This is not to say that having research experience isn't helpful, or that a strong personal statement isn't an asset, but rather that it is generally much easier (and, in my opinion, more reliable) to rank applicants based on other factors like grades and letters of recommendation. This is particularly true in stat/biostat, where meaningful research experience is relatively rare and it's considered completely acceptable for incoming PhD students to not have much of an idea what they'd like to do research on. Overall, the process really isn't that mysterious: we are trying to identify the most talented students, with an eye towards balancing research "upside" with likelihood of success in the program. The strongest predictors of success in graduate school remain grades, letters of recommendation, and to a lesser extent standardized test scores. Nobody wants to hear that because applicants would like to think that they can dramatically alter their prospects by crafting the perfect personal statement, but the reality is that your fate is mostly sealed by the time you come to prepare your application. A lot of people contend that "admissions is a crapshoot," but that attitude is simply inconsistent with the remarkably high intra-individual correlation observed in individual admissions results across programs. With a few exceptions, an applicant who applies to a set of schools of similar strength is likely to get into either all/most of them or none of them.

First, let me say that you are a lock for virtually all Masters programs, especially in biostatistics. For the PhD, I think your profile brings a lot of possible outcomes into play, from being admitted to a couple of the top programs to being shut out of the top 6-10. A lot will depend on the details of your application, including grades in your math classes, strength of letters of recommendation, and perceived prestige of your school. I wouldn't view any biostat program as totally unrealistic, but I think your "decent bets" are schools ranked in the 4-8 range (UNC, Minnesota, Michigan, Berkeley/Emory/Penn), and I certainly like your chances at most places outside the top 10.

Stat and biostat are generally pretty similar at the MS level; the typical program will offer a first-year graduate-level course sequence in mathematical statistics, along with various more applied courses in regression, survival analysis, experimental design, etc. Being in biostat shouldn't preclude you from moving into a non-health science area later on.

It depends on who sends out the decision. If it's a faculty member, a weekend email is certainly a possibility; if it's a member of the administrative staff, a weekend is much less likely.

Is your list all stat programs, or are you considering biostat as well? I think your profile will play much better in the latter than the former.

I think your best bet is to be honest. There's nothing wrong with keeping an open mind about job prospects after a PhD; what faculty generally don't want to hear is that you have NO interest in pursuing an academic path after graduation.

MS applications are sometimes evaluated only after most PhD offers have been made.

Having obscure research interests certainly won't help you; some places care more about "fit" than others, but most will be a bit nervous about admitting someone who seems very motivated to work in a narrow area which isn't covered by department faculty. Of course, if your application is really exceptional, your expressed interests may not matter too much as departments figure they can make it work by either finding a suitable related project or simply letting natural "research interest drift" take its course.

Harvard and Hopkins do interviews -- or rather, they invite students to visit before they have been admitted. UNC, Minnesota, Michigan, and Washington don't interview, and host visit days only for admitted students. Most other schools don't interview domestic applicants, but I've heard of some scheduling Skype conversations/interviews with international students whose first language is not English.

A 161Q should be fine, particularly if your GPA is high.

There will be a decent number of students applying who: 1) Have stronger mathematical/statistical preparation, and/or 2) Have similar records to yours, but attended better-known undergraduate institutions You can work on #1. With respect to #2, McMaster is a good school, but it doesn't have great name recognition. Most people know the "big four" in Canada (UBC, Toronto, Waterloo, McGill) but not much beyond that, so admissions committees may find it difficult to put your performance in context. Hence, it would be very helpful for your letter writers to compare you to past students who (say) attended prestigious U.S. graduate programs. The bar for Canadian students is somewhere between the bar for U.S. nationals and for overseas applicants. The bar for overseas applicants is, basically, insane; the only ones who get into top 6-8 places are very good students at a handful of elite institutions. What's really changed recently is the depth of the domestic applicant pool; a couple of years ago, I would have been pretty bullish about your chances at most programs but now there are many more quality applicants. I don't mean to imply that you have no hope of being admitted to a top 5 program. I think your application will be given serious consideration at good places, but I wouldn't bank on all of them admitting you.

You should try and take courses in probability and mathematical statistics. Those are going to be by far the most useful preparation for graduate study in biostatistics. The applicant pool in biostat has strengthened considerably over the past handful of years; I think you might find it tough to crack the top handful of programs (e.g., Harvard, Hopkins) but you will probably be in decent shape at places like UCLA, Columbia, etc.

A couple of things: 1) It isn't a good idea to try to "sneak" into a PhD program if you have no intention of finishing. Faculty will be disappointed and upset if they discover that you never wanted a PhD in the first place; do you really want these people writing your letters of recommendation? 2) Being a female might give you a bit of an edge if you were applying to pure math programs, where women are very much under-represented. But there are a reasonable number of female students in stat and biostat, so in those fields you're unlikely to get any bonus points for having two X chromosomes. As to race, there *is* an advantage to being a domestic student (some funding is restricted to U.S. citizens and permanent residents, particularly in biostat), but domestic students are predominantly Caucasian so among this group it is far more advantageous in terms of admissions to be a minority.

I've never heard of an interview in a stat or biostat department asking technical questions; typically, the assumption is that they wouldn't even consider admitting you if they weren't confident you had the relevant technical ability or the capacity to pick it up on the fly. Many first-year courses in stat/biostat programs are taught out of Casella & Berger , so that may be a decent place to start if you're looking for a refresher and/or head start on what you'll be learning as a grad student.

And what other formula would you suggest that we use? Getting excellent grades from a good school is a pretty strong indicator that a student is smart and talented. Yes, of course, there's more that goes into making a researcher than stellar grades (that's why we look at letters, test scores, and to a much lesser extent personal statements), but admissions committees are in the business of taking bets on who's going to be most successful, and a student with a proven track record of academic success is usually a pretty safe bet.

Masters graduates from our department typically see starting salaries ranging from 50-75k, while PhD grads who go to industry start at 100-120k.

You are applying to exactly 2 biostat PhD programs in the U.S.; if you really want to do biostat, that isn't nearly enough, particularly as the departments you've chosen are extremely competitive (Harvard) and extremely small (Yale). The main issue you are facing isn't your GRE score (it's not great, but won't sink you) or English studies (not relevant), but your relative lack of mathematical background. I would guess you don't have a lot of math beyond the pre-requisites, plus you are international, so you are going to face an uphill battle to be admitted to most top 10 departments.