garmungo

For those of you who may still be looking for a place from a distance, I just committed to a place next to campus that seems like a good deal (I live in San Francisco currently and couldn't take a look at places before renting them), and has some additional rooms available (the woman who owns it rents the rooms individually). Might be worth checking out (PM me if that sounds good). Or, hopefully this is allowed... http://annarbor.craigslist.org/roo/3864081286.html

I'm also heading to Michigan. Looking forward to potentially seeing/meeting all of you in the Fall.

I just visited UMich, and can offer the following advice: 1. My understanding is that if you speak and read english well, a TA position is very likely. 2. Your best bet here is to check out listings on craigslist.com, or simply look online for houses for rent in the ann arbor region near the university. My guess is that these won't be too expensive, but the best way to find out is to simply get on google and search.

This thread is of particular interest to me, as I also have an admit from Michigan's MA program and I also am interested in getting some (or a lot of) Machine Learning exposure. I've been leaning towards UCLA over UMichigan because it seems to be a bit more flexible and potentially more rigorous (but hell, what do I know?). That being said, Michigan seems to be a much higher-ranked and higher-regarded program. Anyway, here are my impressions of the Michigan MA Applied Stats program at the moment (for what they're worth): I researched ~16 randomly-selected alumni from the program that have graduated in recent years. I was able to find information on all but 2 of them. Of the 14 remaining, 11 of them definitely seem to have had TA positions, so it does look like getting such a position is fairly likely if you try. Also, almost all of the 14 seem to have gotten positions following graduation, of which I made the following generalizations: Most had titles like statistician or biostatistician Most got jobs in the Michigan area ~2 went on to PhDs ~2 went into finance (ibanking in one case, risk officer in another case) As near as I can tell (and, again, I basically *can't* tell), none are doing anything ML-related For the program itself, I noticed that there are a few places to customize your degree outside of the regular coursework: You get 3+ electives, all of which (as far as I can tell) need to be taken in the Biostatistics/Statistics department. These are pretty flexible, assuming you choose something in their pre-made list or something above course level 600+ (I assume higher numbers = more advanced classes). From what I can tell, you are required to take 1 cognate course, which can be in any department, so long as you get it approved by the stats department. It looks like it's possible to fit in a second cognate course, but I'm not sure how difficult that is along with the rest of the degree requirements. This is where I'd think you'd be able to take a CS class or two in Machine Learning or a related topic (though there is one 600+ stats class that can be taken as an "elective" that touches on Machine Learning as part of the coursework). To conclude, Michigan has a great reputation for Machine Learning, but it appeared to me at least that getting a significant amount of ML exposure would be difficult in this particular program given the low number of cognate courses. Hopefully this was helpful. I'm planning to visit Michigan soon to hopefully find out more, and can potentially report back once I do that. Please let me know if any of the above looks wrong, as it's what I'm basing my decision on at the moment (and I don't want to base my decision on bad data!). I'd love to hear any other thoughts.

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'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.

Hi everyone, I joined up because I recently applied to Masters programs in Statistics. Namely, the following programs: UMichigan (accepted) UW Stanford UCLA Stanford or UW would be my top choices, but I haven't yet heard anything from these programs, so I wanted to ask about how the UMich program stacks up. I know the PhD program at UMichigan is strong, but given that this is an MA (not an MS), I'm concerned that maybe the MA in Applied Statistics at Michigan isn't as strong. I'm interested in things at the intersection of computer science and statistics (eg. machine learning), so it SEEMS like it would be a great choice...but does anyone have any opinions/insight on this? Namely, does anyone know if this program has the same great reputation that the PhD program does? Thanks in advance!