MS in statistics: Washington vs Toronto

[jt0622]

Hi,

 

I am an international student accepted to both MS in statistics of U of Washington at Seattle and U of Toronto, and I haven't decided to do PhD or to find a job afterwards. I am wondering if anyone could shed some light on each of these programs.

 

The MS program at U of T is fully funded with extra scholarships, but the program is short (1 year). Is the short course duration a big disadvantage? Although there are a few professors there that I am familiar with (so probably I can start my research projects early), I realize a PhD right after my master is virtually impossible to get since applications will have to be submitted 3 months after I begin my master, which isn't enough time to do anything significant. I am also confused with how important the scholarship I get in master is in applying for PhD. 

 

The MS program at U of Washington is without any financial support and it is for two years, giving me more time for meaningful research. The program is highly ranked in the states, and UW is quite famous for machine learning, which is one of my interests that I want to do in either PhD or job. I am wondering which university is more academically prestigious in statistics (it is hard to find a ranking for both Canadian and US universities). 

 

Could someone please shed some light on my questions? Thanks in advance!

[essequamvideri]

2 year unfunded master's = a lot of debt. U of T has great machine learning faculty. Personally, I'd say this is a no-brainer and I'd go for U of T.

[MathCat]

I don't even like U of T (personal preference only - I can't stand Toronto) and I'd still say it's a no-brainer for taking U of T. I don't particularly like the 1 year program either, but funding is hugely important. Go with the funding. U of T is also very well regarded.

 

You can still get into a PhD right after if you want to - you would probably use 1-2 references from your undergrad because you wouldn't have much time to get a meaningful letter from anyone at U of T, but that's alright. I don't know about the stats program, but I know in math, U of T often retains many of its Masters students for PhD studies there - it's often a lot like a direct-entry PhD in the US.

[MLHopeful]

Washington stats as a hole is certainly more prestigious, and between the two PhD programs there would be a meaningful drop-of in terms of prestige and caliber of student. That being said, Canadian masters are generally far more research-oriented then US programs, so UofT may provide a better opportunity to do meaningful research, if that's what you want to do. This would be better for a potential PhD (I'm speaking generally as I'm not too familiar with the particular programs). I met a few students who did their masters at comparable Canadian schools and got into top-5/10 American PhDs, so that can be done - although the one year degree may prove tricky. The UofT deep learning group, led by Geoff Hinton (how's now at Google part-time), is world-class, so if you could work with them I'd go there.

[wine in coffee cups]

I would take the fully funded option. Where did you get the impression that you would be able to do "meaningful research" in the UW master's program? It's a coursework-only degree with limited opportunities for research.