twilightgalaxy

I'd say UW, UNC, and maybe Michigan.

Hello fellow Canadian! Yes, it is generally harder for Canadians to get in compared to US applicants, but IMO it's not an extremely huge disadvantage, especially if you are from a school with any name recognition (which evidently you are). Also, in my limited experience talking to other Canadians, the feeling is that some schools just tend to accept more international applicants than others, so that can have an effect as well. I don't have a lot of experience evaluating profiles, but your list looks reasonable to me, and I'm sure you'd do fine applying to Stat/Biostat MScs in Canada. Or PhDs - I seem to recall UoT Stat had a PhD program that accepted applicants without MScs. You're at a school which has sent students to some good schools in the last few years - I know of students at Berkeley, CMU, UW, etc. from those schools, so I bet members of your department have some good advice about which schools to apply to. I would look there first for advice.

Re: odds of transfer, you should consider that not all MS students wish to transfer to the PhD. Anecdotally, everyone I know who wanted to transfer to PhD (as you said, 1-2 students of a small cohort) managed to do so. Of course, I could have missed people who wanted to transfer but did not get in. I'm sure there's issues of selection too, in that better students are more interested in doing PhDs. But just something to consider.

Maybe something like 30% research, 60% coursework, and 10% seminars (no teaching duties).

I went from undergrad straight into a Biostat PhD and very few of us, if any, had very concrete idea of research interests. It's definitely not expected that you know what your dissertation topic or even area is going to be from the get go. If you have a few areas that you're interested in (even if you don't know too much about them!) you'd probably be on the same page as a good amount of other applicants. I don't think you'd have a problem applying to PhD programs. It's also worth noting that most Masters programs don't guarantee funding, while PhD programs generally do. My feeling is unless you want to improve your profile in order to try for better PhD programs, if your long term goal is a PhD you should apply for the PhD. It's worth noting though that Michigan is a notable exception, since they offer funding for the Masters and do not do direct admits into PhD from undergrad as far as I know.

Since you're not getting much traction from any actual math majors, I guess I'll throw in my two cents ;P Between abstract algebra and real analysis I would've taken graduate real analysis hands down. I find in the types of math papers I have to read (optimization, engineering and statistics) familiarity with basic concepts in analysis (especially measure theory for anything probabilistic) helps while despite taking 2 semesters of abstract algebra I can't say that I've ever used it. I know you didn't want answers that depended on future plans, but I'm going to take a crack at it anyway. For grad school in Math, at least in Pure Math, my impression is that algebra and analysis are both super core topics, so I'm not sure how to swing on that. For probability/stats and I would guess engineering, real analysis is much much more useful.

My cohort seems pretty evenly split in terms of having Real Analysis vs. not having Real Analysis. I feel that it's definitely good to have, both in terms of future development as well as for grad school applications, but not having Real Analysis is hardly going to automatically disqualify you from top programs. I'm no applications expert, but if you could get some significant research experience and results out during the summer, I would suspect that would help you more on the application especially if you have taken any other strongly proof-based mathematics courses to help cement your mathematical ability.

Undergrad Institution: Mid-sized Canadian Research University Major(s): Mathematics and Statistics GPA: 4.0 Type of Student: Canadian Female GRE Revised General Test: Q: 169 (97%) V: 168 (98%) W: 5.5 (98%) GRE Subject Test in Mathematics: M: N/A Program Applying: PhD Biostatistics, MSc Biostatistics, PhD Statistics Research Experience: 2 full time 4 month RAs and 1 part time 8 month RA in Statistics. 1 publication, 1 accepted publication, one conference talk. Awards/Honours/Recognitions: Mostly academic awards, some awards for posters/presentations etc, large scholarship for undergrad. Pertinent Activities or Jobs: TA for 2 years, marking and tutoring. Letters of Recommendation: A stellar one from the professor who I wrote two papers with, two great ones from other Stat professors at my school. All are senior, but not really well-known. Any Miscellaneous Points that Might Help: Took a lot of cross-listed Master's classes in Statistics. Applying to Where: University of Washington - Biostatistics PhD - Accepted January 9th (Attending!) UNC - Biostatistics PhD - Accepted January 8th Harvard - Biostatistics PhD - Rejected March 11th University of California Berkeley - Statistics PhD - Rejected March 11th University of Toronto - Biostatistics MSc - Accepted March 14th University of Waterloo - Biostatistics MSc - Accepted February 2nd