cyberwulf

UW is a bit weird in that their Masters program is pretty small, and it seems like most of their MS students are local to the area. Hard to know what your chances would be like getting in there. As far as solid Masters programs in your neck of the woods, I would consider adding Columbia and Brown to your list. I would consider both to be stronger than BC, Pitt, and FSU. Boston University is another place to look into.

Davis is a solid stat department, but they aren't known for biostatistics. Don't know much about UCSC. If you're looking at other places in the Bay Area, it might be worth checking out UCSF. I noticed that they've just started a new PhD program in Epidemiology and Translational Science: http://www.epibiosta...s/doctoral.html As a general guideline in searching for biostat programs, you're usually better off looking at institutions which have a medical school (Berkeley being the notable exception).

You don't NEED research experience to get into grad school, but the only other way to get strong letters is if your grades are excellent.

I would apply to Berkeley biostat. It sounds like you want to do biostat, and Berkeley stat is pretty theory oriented. Lacking a biostat deparment, Stanford has a strong group of biostat folks on the stat department, so they are worth considering as well.

Why not just apply to Stanford stat and see what happens? An MS from NCSU and 6 years research experience are nothing to sneeze at...

There are two excellent departments of Biostatistics on the West Coast: Berkeley and the University of Washington. Berkeley is a pretty small department (< 15 faculty, probably about 5 incoming PhD students per year), but Washington is huge (> 60 faculty, > 20 incoming PhD students per year). UCLA has a solid department, but not on the level of those two places. Stanford is a great place with several faculty doing biostat-oriented work, but it's a stat department so the applicant pool looks quite different and it will be much harder to get into. Same applies to Berkeley stat. The relative difficulty of getting into MS and PhD programs varies by school, but in general it is much easier to gain admittance to an MS program because funding is generally not offered. While having an MS can make you a stronger candidate for PhD admission, you have to be careful because some MS programs offer little or no mathematical statistics and hence don't significantly improve your chances. Doing such a "preparatory" MS is a good idea for those who are really unsure whether graduate study in stats/biostats is for them, or if your previous academic record is too weak to make you a viable candidate for direct to PhD admission (in which case stellar performance in a Masters program could alleviate concerns about your readiness for further graduate study). If you decide to do an MS with an eye towards a PhD, you really need to get yourself into a top 10-15 stats or top 5 biostat masters program; good performance at a weaker program doesn't give an adcom much information beyond what they can gather from your undergraduate record and letters.

Shostakovich, not having research experience or an MS should not be a major barrier to being accepted into a PhD program. Many programs do not require a previous Masters for PhD admission, and most that do have a "fast track" pre-doctoral MS option with some funding available. It sounds like your undergraduate background and grades would be competitive for PhD admission at some good places (depending on where you did your undergrad, what your rec letters are like, etc.), so you should probably consider the direct-to-PhD route if a doctoral degree is your eventual goal.

The scores you're quoting for Harvard have got to be for the MS program; I'd be very surprised if the median GRE Q for PhD admission at Harvard biostat is not 800. Here's the deal on the GRE components, at least from one faculty member's (i.e. my) perspective: - To be considered for most top departments, you're going to need a GRE Q better than 750 (roughly 158ish in the new system). Many people applying to good PhD programs will have GRE Q scores of 800 (> 167 in new scoring). You can't really help yourself that much with your GRE Q score, but a mediocre score can hurt your chances. - The Verbal score doesn't matter very much. Many foreign students whose first language is not English score much better than U.S. students, so clearly it's possible to "study up" the material and perform well. That being said, a truly excellent verbal score (eg. one in the 95th+ percentile) may work in your favor as an indicator of general intelligence. Mediocre verbal scores are commonplace among biostat applicants (even at the best programs), so unless your scores are truly disastrous (think 30th percentile or below) I wouldn't worry about it. - The Analytical Writing score has virtually no variability among typical applicants; almost everyone scores in the 3.5-4.5 range. Hence, it's essentially ignored. A 6.0 could help you stand out a bit, but not much.

Your top 4 schools are reaches for (funded) PhD admission, but you'll probably have a decent chance of getting into their MS programs. I would expect that you would have some success if applying to PhD programs at schools like Pitt, NC, and FSU. If you decide to pursue the MS instead of a PhD, the name and reputation of the program you choose isn't as important as it is if you go the PhD route.

If you already have training in statistics, I would go with biostatistics. One advantage of biostat is that you can keep your options relatively open in terms of the types of problems you want to work on. I don't think a PhD will limit your job options tremendously; plus, there's an opportunity to get funding in PhD programs.

While a Q155 isn't great, I don't think it's disastrously bad, particularly if you're looking for an MS at a local place like Rutgers/UMDNJ. You might consider calling the departments you're interested in to see if they'll tell you what the mean/median GPAs and GREs of entering students are; this should give you a good idea of how high you can aim.

Sisyphus is right. My advice is more applicable if you were looking to apply for PhD programs.

At minimum, you'll need linear algebra, multivariable calculus, mathematical statistics, and probably real analysis to have a serious shot at good stat programs. Unfortunately, SOA exams won't mean much to stat adcoms, but you might get more credit for doing well on them if you were applying to ActSci programs.

That list looks just about right to me; the places at the top will be tough (though not impossible) to crack, but I suspect you will have a pretty good success rate from the middle of the list on down.

Most introductory books on biostatistics are really just basic statistics texts designed with medical/public health students in mind. The core topics are typically very similar to any usual stat textbook, but the examples are more medical/biological in nature. Most first-year biostats students will already have had an introductory stats course, and so will not be using these types of books. They will usually take a mathematical statistics course along with several more specialized applied courses (linear regression, categorical data, survival analysis, etc.), each with their own domain-specific reference. It sounds like you want a book that will give you a survey of the types of projects biostatisticians work on. I don't know of a good book of this type out there. A student in one of my classes recently brought the following book to my attention: http://www.amazon.co...g/dp/0199730067 . I haven't looked at it carefully, but it might fit your bill.

I would recommend that you keep your options open and not cross any schools off purely based on perceived research "fit". First, it's usually difficult to find out enough about who's working on what to make a fully informed decision. And second, many PhD students end up working on something very different than they envisioned when they were applying to graduate school, and if that happens, you're better off at a place that provides lots of high-quality options (i.e. a top-tier institution). Also, I think that list you have is pretty reasonable; if your letters and test scores are consistent with your academic record, I have a hunch that you won't need any additional safety schools.

By the way, the above advice applies to PhD programs. You should probably apply for PhD instead of MS for funding reasons.

I think you'll have a good chance at admission at most of the places on your list. Harvard might be a stretch because their applicant pool is so large and strong, but everywhere else is within reach.

Have you taken a course in mathematical statistics? If not, you might consider grabbing a copy of Casella & Berger and reading though it. It's pretty much the canonical book for a first-year graduate math stat course.

Particularly in biostatistics, research experience means very little because so few students have the statistical background to do anything useful before they reach graduate school. Furthermore, the applicant pool in biostat remains relatively shallow, such that one can generally establish clear candidate rankings based on transcripts, letters, and standardized test scores. This is in stark contrast to medical school (for example), where adcoms are faced with hundreds of students who all have pretty similar profiles, and research experience can be one way to distinguish yourself. Few programs enroll more than 50% of the students they offer to on a regular basis, so most will offer at least 2n to get n. A good rule of thumb on the number of spots that a program has each year is to divide the total number of PhD students in the program by 4, and the number of Masters students by 2.

Congrats on making such a strong academic 'comeback' after some early difficulties. Admissions committees tend to be sympathetic towards initial struggles if later results are much improved. That being said, how high you can reasonably aim depends a lot on the perception of your current institution. If it is little-known, there may be a question of whether your excellent grades are due to the fact that you've gotten your act together, or rather a lack of academic competition. You will definitely want to address the discrepancy between your initial and more recent academic performance in your personal statement; if you didn't apply yourself then but feel that you have now matured, say so! Letters of recommendation are going to be very important for you. I disagree with the above poster about the importance of SIBS (having participated will have little impact on your chances of admission), but I concur that it would be a good idea to try to distinguish yourself enough to get a strong letter from a faculty member at NC State. You probably have a good shot some fairly good Master's programs, and (depending on letters and transcript) perhaps some PhD programs as well. If you're thinking about going directly to PhD, you will probably be able to aim a bit higher (eg. top 10) in biostat than stat departments.

Lots of good advice on this thread already. OP, if you maintain some interest in medical science but think you're more quantitatively oriented, you might also want to look into programs in biostatistics. The top places offer similar theoretical foundation to good stat departments, but the admissions requirements tend to be a bit lighter on the math (Calc 1-3 and Linear Algebra are usual pre-requisites).

Don't bother. Not because they'll think the work isn't worthy, but because with 100+ applications to get through, chances are they won't have time to look at it. Best way to "use" that project is to have your letter writers talk about it.

Do you want to study pure math, or are you looking for something with a more applied flavor (eg. applied math, biostatistics)? This is going to affect the relevant advice. Stat/biostat graduate programs will require, at minimum, multivariable calculus and linear algebra; many stat departments also require a first course in real analysis. Math programs will require quite a bit more; think abstract algebra, topology, complex analysis, and differential equations.

In my opinion: UW (Seattle) >> UW (Madison) > UF > GW UF Biostat, while little-known, is an up-and-coming department linked to a strong stat group. It may not be too long before the ">" between Wisconsin and Florida turns into an "=".