cyberwulf

Writing a paper with only a Masters degree could be a tough task, unless you're doing something rather applied (in which case it would be odd to not be collaborating with subject-area experts). Why don't you get in touch with a professor in the program to see if they might be interested in working with you during the summer? Some stat journals (eg. JASA) have a blinded review process, so that there is a non-zero probability that your paper will be judged on its merits and not the author list. If you really want to go it alone, I would submit to one of those.

I guess it depends on the level of place you're aiming for. The problem is, there are so few pre-requisite math classes (Calc I-III, Linear Algebra) that admissions committees don't have a lot of grades to look at and so the influence of each one can be sizable.

No question, retake Multivariable Calc. A B- in a core math course could sink your application, but having (or not) Environmental Statistics will make virtually no difference.

mathgeek is right. For better or worse, sports statistics is not viewed as a "serious" sub-discipline of statistics (as opposed to polisci stat or industrial stat, say) by the vast majority of academics. True, a number of well-known faculty members have written about sports, but these are mostly "hobby" papers that don't enhance their academic reputation.

Take as much math as you can as an undergrad, with a pinch of CS and stats. Top Biostat grad programs love people with strong quantitative backgrounds; you can pick up the bio/applied bits later. Though both are great programs, one (small) advantage of UW over Berkeley is that UW Biostat is a huge department ranked in the top 3 nationwide. Though it's only a graduate program, you might be able to find opportunities for summer research if you poke around.

You can apply directly to PhD programs in biostatistics out of undergrad; typical minimum requirements are Calc 3 and Linear Algebra, and some exposure to probability/mathematical statistics. More math is generally better (you'll be relying heavily on the strength of the rest of your application without it), so see what you can pick up. Re: where/how to take classes, we frequently see students who have taken math pre-reqs at places like community colleges or random local universities while they were home for summer break. I don't think a distance education course would be treated any differently than that (i.e. we're totally fine with it, though the bar for acceptable performance has to be adjusted for class strength/rigor).

This isn't the first time that UofT has had to process an application from someone in Quebec; I'm sure they have a system. That said, it wouldn't hurt to follow up to make sure that everything is proceeding as anticipated.

In many fields, this "3.9+ GPA required for admission to top places" claim is demonstrably untrue. First of all, undergraduate institution matters a *lot*; no adcom in their right mind would take a student with a 3.95 from Random Third-Tier State U over a 3.75 from Harvard (all other aspects of the application being equal). Second, other parts of your application can also carry a lot of weight. In some fields, research experience is key; or very strong letters; or a compelling personal statement; or standardized test scores; or grades in particular classes. It's a cliche to talk about the evaluation of applications being "holistic", but for graduate school it really is (perhaps moreso than for undergraduate admissions). This is not to say that people with great top-line numbers aren't rejected by good (and even less-good) places, but simply to point out that GPA doesn't tell the whole story.

I'm sure UF and Georgetown work the same way with respect to research and teaching assistantships: there are a limited number, with priority going to PhD students, so Masters students may or may not be able to land one every semester.

While changing your mind (BEFORE April 15) is technically allowed under the Council of Graduate Schools resolution, the department whose offer you are changing your mind on would have every right to be upset. Depending on your future academic plans and the size of your field, their negative feelings about your behavior may or may not matter. Changing your mind AFTER April 15 is a big no-no.

If you *really* want to do theory, you should probably go to a stats department. What distinguishes programs is *selection*, on two important dimensions: 1. Selection of research topics. Most faculty in stat departments work on theoretical topics, most in biostat on methods/applied topics. 2. Selection of "high-profile" advisors. Higher-ranked programs generally have a larger number of "famous" advisors whose name and research program will get you interviews at elite departments. Lower-ranked programs may have only one or two (if any!) such advisors, so you may be limiting your "upside" if you attend these programs, particularly if the handful of "big name" faculty are very busy or nearing retirement and not willing to take you as a student.

Some truth. I would avoid explicitly mentioning that you have no interest in pursuing academia.

Lack of research experience is not going to hurt you. Few people have much of it prior to applying to stats/biostats programs. If 'name' is important to you, I would consider adding Johns Hopkins biostat to your list.

Masters programs are generally unfunded. Sometimes this just means that though they can't guarantee anything, there's a decent chance you'll be able find an RA/TA when you show up. You should probably contact UF to find out what the typical 'unfunded' experience is like.

This isn't at all surprising; NCSU is a stat department and hence requires more theory. You don't need Real Analysis to be a Masters biostatistician, but if you're looking to continue on for a PhD you'll need to take it at some point.

Assuming you want to work as a biostatistician, I would lean towards the MS in Biostats at UNC. UNC is recognized as an elite biostatistics department, while NC State is better known as a (somewhat applied) statistics department. It looks like the course offerings are essentially the same, so you're likely better off in the department which specializes in the topic you want to study.

If the schools involved abide by the Council of Graduate Schools' resolution, then you should be able to switch without any repercussions prior to April 15.

Your advisor may be behaving this way because he is desperately hoping that you'll stick around to do a PhD, not because he assumes that's your plan. It's a common "trick" of departments (particularly those that don't get the most talented PhD students) to identify talented Masters students and then strongly encourage them to continue on in the PhD program at the same school. They often do this because they are worried that if you apply elsewhere, you're likely to get in and be enticed to leave for a more prestigious institution.

Centurion is right on. In fact, you'll be giving the schools useful information by letting them know they didn't make your "shortlist".

I think the preferred option would be to contact the schools that haven't offered you funding and just ask if it's OK for you to let them know after April 15. If the other schools don't have money riding on your decision, it's unlikely that they'll mind waiting a few more weeks to hear from you.

It's true that Masters degrees are increasingly perceived as money-makers used to support PhD programs. I don't know if this is the motivation for the program changes at Berkeley, but just because a school turns a profit on your studies doesn't mean you won't have a good experience. The key question is: What are you getting for that extra money? I think it's entirely legitimate for you to request clarification from someone in the department as to what the changes will mean for the student experience. If they can't give you a straight answer, you might want to think carefully about whether you want to pay for the privilege of being a guinea pig as they develop their new model.

I've said this before in other threads: It's hard to go wrong by asking "So, what are you currently working on?" This question doesn't get asked nearly often enough by visitors; grad students and profs usually *love* to talk about their work.

Don't worry about whether a department has a formal course on machine learning/data mining. What matters is the presence/absence of faculty who work in the area.

A more common text for first-year stat theory courses is Casella and Berger.

I think it's pretty crummy for a department to have any sizable fraction of graduate courses taught by other graduate students. Grad students can be good *lecturers* (because they often put more effort in preparation than faculty members), but they are unlikely to have the knowledge and experience to be truly excellent *instructors*. One of the most important parts of grad school is engaging in the material beyond the classroom, which is difficult if the teacher has only a marginally better grasp of the material than you.