MS in statistics: Washington or 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!

[Fedra]

How important is the funding for you?

UW has a very prestigious program, not everyone is accepted there. Additionally, if you go there it would be easier to get a funding PhD

[smpalesh]

Not everyone is accepted at U of T either...  It is ranked 16th in the world so it is pretty prestigious.

[nugget]

Not my field, but if both programs are comparable in terms of ranking, I'd go with UW if lack of funding is not important to you. If you need to take out a loan or if it would be a struggle to come up with the funds, then go with U of T.

 

If you stop after a masters, a 2 year program would likely give you more preparation for the job market. If you go for a PhD, you would also be more prepared and it would look better to admissions committees to be in the longer program (assuming you make the most use of that extra year in school and have something to show for it).

 

If you think your odds of getting into a good PhD program won't be compromised by a 1 year masters (if the program is a great reputation and if it's enough time for you to amply build your cv), then I think you should seriously consider it.

 

(That being said, I personally would take it. Why pay for an education when you can get one for free? But that's just me because I hate debt).

[MathCat]

This is largely cross-posted from the Math & Stats thread, so I'll cross-post part of my answer from there: 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. Also, if you wish to apply to other programs, you can still use some LORs from people from your undergrad. Many people do 1 year Masters programs at places like U of T or U Waterloo and then go straight on to PhD programs.

 

Regarding research, I had the same concerns (I also considered 1 and 2 years masters programs, although I'm going to a PhD program), and professors assured me that you don't get into much real research in a Masters either way. Although the 2 years is definitely better, I don't think it outweighs funded vs. unfunded considerations.

 

You usually do better in the academic job market coming from the US than coming from Canada, but that applies more to PhD programs than Masters. Unless you have the savings to fund yourself for the UW program (including the high cost of living in Seattle), I'd say go to U of T. It's not worth taking on debt when you have a good funded offer. U of T is definitely among the top schools in Canada, and is considered by many to be the top school. I don't know about the statistics ranking of UW, but U of T is ranked higher in math than UW is.