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Statistics Masters: University of Michigan or UCLA


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I'm trying to decide between these two Masters programs:

 

MA Applied Statistics UMichigan

MS Statistics UCLA

 

I'm leaning towards UCLA at the moment, but I want to make sure I'm not missing anything.

 

In a nutshell, I'm most interested in machine learning and its applications, which, if I were doing a PhD, sounds like UMichigan is best for.  However, the UMich masters program doesn't seem to allow as much flexibility/cross-department classes as the UCLA masters program.  On the other hand, I've seen some vague UCLA-bashing on a few forums (only someone looking for it would find it), so I'm concerned that this is somehow a much less reputable program.  Lastly, it looks like Michigan is significantly higher on the rankings (not sure if this matters a lot, a little, or not at all).

 

Other considerations are: UCLA is an MS, which I view as being "better" than an MA.

 

Does anyone have an opinion on this they can share?  I'd really appreciate any thoughts/advice.

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I would definitely go for U. Michigan if I were not accepted by U. Chicago. Ranking in stats area, job placement, preparation for PhD, TA-opportunity, cost of living, Michigan beats UCLA in all of them. Of course, it would nice to live in Cali with sunshine all year long and LA is a paradise :)  

 

I am not trying to say it would be a terrible mistake to choose Michigan over UCLA. It depends on what u want after masters. My cousin (international student with US undergrad degree) actually graduated from UCLA's stats masters program last Aug.and his experience was that masters students do not get much or none attention from Profs or the dept. And it's quite a small dept with heavy focus on computational statistics if that interests you. He is now doing another masters in fin. math at NYU simply b/c he cannot land a job after graduation. He told me he regrets a lot for the tuition and high cost of living paid for 2 years' UCLA life lol.

 

Hope that helps.  

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Thanks for the info statsmasters.  I'm also leaning towards UCLA right now, but my other options are Johns Hopkins (masters) or Bowling Green (PhD).  Knowing that your cousin is having a hard time finding a job is giving me second thoughts, since I'm going back to school specifically trying to improve my job prospects.  Do you know how common it is for UCLA students in the masters program to go on to get a PhD?

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If you could be accepted off Chicago's waiting list your choice would be clear. Just so you know Chicago's program is very theoretical and most of their masters students continue on to PhD after graduation. 

 

As far as my cousin knows, in his class two students (computer science undergrads) found consulting jobs at start-ups. He knows one student (math undergrad) continued to PhD at Minnesota. A few international students chose to do another masters just like my cousin due to being unable to find employment. 

 

If you like computational stats then I would say go for UCLA. If you like biostats, JHU no doubt. I don't know much about JHU's program but its stats dept. seems to be very reputable. There are definitely more jobs for statisticians in the east coast. Another thing you might want to consider is the cost. My cousin paid a scary number (at least for me lol) for his entire two-year UCLA life. If money is not an issue you will have a good time in UCLA for sure.

 

Good luck! 

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Wow, more great info.  Thanks again.  With respect to cost, tuition at UCLA for 2 years is about $45k (assuming out-of-state first year, in-state second year), while tuition at JHU for two years is about $90k ($45K a year for 2 years), so UCLA seems dramatically cheaper.  I don't know if cost of living is that much higher in LA than Baltimore, but maybe it is,  That's actually one of the reasons I was leaning towards UCLA.  I told Chicago to keep me on the waitlist, but JHU wants a decision by April 15th and I doubt I'll hear from Chicago before then.

 

Tuition Sources:

http://www.gdnet.ucla.edu/gss/library/1213gradfees.pdf

http://www.grad.jhu.edu/admissions/cost-financial-aid/index.php

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Hi Statsmasters,

 

Thanks very much for replying.  Really helpful information.  I'm actually a current resident of CA, so tuition at UCLA is actually much cheaper ($15K/year).  That being said, I did a run-down of the last 20-ish UMich Applied Masters graduates last night, and almost all of them seemed to have gotten TA jobs, which (I believe) means their tuition was waived.

 

I'm most interested in doing things at the intersection of statistics and computer science, specifically machine learning or computer vision (there's a vision lab at UCLA), but I'm interested in computational statistics as well (and from what I can tell the two fields are very related).  So, in that regard, UCLA seems like it would be a great fit.

 

After a lot more research last night, I think I'm still most excited about UCLA because their Masters program allows for more flexibility, meaning I could take computer science AND statistics courses.  The Michigan program doesn't seem to be as good a fit (despite all the great things about it you pointed out).

 

My main and only concern at this point (and your comment about your cousin's experience hit the nail on the head) is that the UCLA Masters program is somehow less reputable than I believe.  I'm fairly certain I'm overanalyzing, but I basically just want to make sure I'll have opportunities to get time with professors during the program and that the program is reasonably well "thought-of" in industry and/or at other PhD programs (in the event that I go that route).

 

Sounds like I should start talking to current Masters students and recent grads (and trying to figure out if they all had similar experiences to your cousin).  If anyone sees any red flags or has any comments on the above, let me know.  Again, thanks very much for sharing and for helping me figure things out!

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Thanks for the info statsmasters.  I'm also leaning towards UCLA right now, but my other options are Johns Hopkins (masters) or Bowling Green (PhD).  Knowing that your cousin is having a hard time finding a job is giving me second thoughts, since I'm going back to school specifically trying to improve my job prospects.  Do you know how common it is for UCLA students in the masters program to go on to get a PhD?

 

 

Looks like his cousin's an international student though. Job prospects are tough for most non-citizens/PR's even for many MS holders due to problems like visa/green card sponsorship and sometimes language barrier.

 

Hi Statsmasters,

 

Thanks very much for replying.  Really helpful information.  I'm actually a current resident of CA, so tuition at UCLA is actually much cheaper ($15K/year).  That being said, I did a run-down of the last 20-ish UMich Applied Masters graduates last night, and almost all of them seemed to have gotten TA jobs, which (I believe) means their tuition was waived.

 

I'm most interested in doing things at the intersection of statistics and computer science, specifically machine learning or computer vision (there's a vision lab at UCLA), but I'm interested in computational statistics as well (and from what I can tell the two fields are very related).  So, in that regard, UCLA seems like it would be a great fit.

 

After a lot more research last night, I think I'm still most excited about UCLA because their Masters program allows for more flexibility, meaning I could take computer science AND statistics courses.  The Michigan program doesn't seem to be as good a fit (despite all the great things about it you pointed out).

 

My main and only concern at this point (and your comment about your cousin's experience hit the nail on the head) is that the UCLA Masters program is somehow less reputable than I believe.  I'm fairly certain I'm overanalyzing, but I basically just want to make sure I'll have opportunities to get time with professors during the program and that the program is reasonably well "thought-of" in industry and/or at other PhD programs (in the event that I go that route).

 

Sounds like I should start talking to current Masters students and recent grads (and trying to figure out if they all had similar experiences to your cousin).  If anyone sees any red flags or has any comments on the above, let me know.  Again, thanks very much for sharing and for helping me figure things out!

 

 

I can't speak for the Stats program because I don't know much about it, but I've done a lot of research on their Biostats program and it seems to be quite reputable. Their Stats department seems to be similarly ranked (a little higher actually) and all their MS students have advisors so there's definitely some student-professor interaction.

 

I would choose UCLA over JHU (but not Chicago) because of the cost. 45K of savings (or 60K for CA residents like us from what you said) could go a long way, and may be an encouraging factor in deciding to pursue PhD later on :) Good luck!

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