Robbentheking

Michigan is really good so I wouldn't put too much into that. But I second the comments about randomness in the applications, as well as the idea that some schools would not send an admit if they think you won't go.

This is probably not helpful, but I do know someone who was accepted off the waitlist a couple years back. It's not a black hole with probability 1.

For sure. I meant this figuratively, in the sense that you get paid to understand things that (hopefully) interest you, whereas at an industry job, learning what interests you is not your main work.

A ridiculous exaggeration. I have an MS in stats, and got acceptances from CS PhD programs despite only taking algorithms, complexity theory, and deep learning during my MS, and not taking any CS courses in undergrad. If you're studying ML, which is presumably what OP wants to do, they wouldn't care if you don't know how change the working directory in your terminal if you have a decent math background. 'PhD in Statistics & Data Science'. He is clearly interested in ML, which is something that takes place both Statistics and CS departments. The idea that anything I said is off topic is also ridiculous. If you think someone truly interested in anything is going to be satisfied with 5 minutes of additional knowledge from Wikipedia, I have nothing to say. Try holding a full time job and keeping up with any current literature in a meaningful way.

Lol, how does it not accomplish the goal? It's not a necessary condition, but it's certainly a sufficient one. In a PhD program, you can get paid a living wage to read Wiki all day, every day. As far as Statistics specifically, obviously it's up to OP to pick a department that suits his/her interests.

Full disclose: I have not worked in industry as a data scientist and my opinion is just from word of mouth. I think people that say that PhD's get the same data science jobs as MS students are not totally correct. Certainly this can be the case, but if you are motivated to work hard in your PhD and prove you have more research ability than being a package-calling coding monkey, my impression is that there definitely are roles out there for PhDs that are more 'interesting', and not just at the hyper-competitive facebook, google, etc. For example, I know from a friend that Grubhub has research teams that do different work than he does as an MS graduate. More importantly, I think it's certainly possible to enjoy a job like your current one further if you have a deeper understanding of the methods you're using, and still more importantly, I wouldn't care about losing out on 5 years of earning potential if you're fundamentally unhappy at the moment. Anyone who goes into a PhD thinking 'this is a waste of time if I don't get an academic job' is really putting themselves in a bad position. Academia is way too competitive for that.

If your interest is theoretical machine learning, TTIC is comfortably top 10. Nati Srebro and Avrim Blum have both done important work in this area, and seem like very good advisors. David McAllester is a bit of a legend in this area too, although his interest has drifted a bit recently. It's hard to say that overall it's a top 10 department in the sense of, say, USNEWS, given that there is essentially no stuff like systems research there. But seriously, in ML, anyone with a UCSD or USC offer and a TTIC offer, as was suggested above, should absolutely take TTIC, unless there is a very specific research fit with faculty at the other schools. I have some inside experience with TTIC for anyone that's interested, and would be happy answer questions via pm.

It really would make more sense imo if people asked questions and had admissions related correspondence in the forum instead of on the results page. there's a lot of non-results there right now haha

I would definitely reply. 'Thanks for the good news. Hope to talk more soon' or something like that.

I think so. If you barely prepared for the test, you should not too painfully be able to increase the quant a few valuable points. Getting into a PhD at "top schools" may be challenging depending on your definition of top schools, but I think you have a place somewhere for sure.

Holy shit dude. I feel so bad for you. I'm pretty surprised that even with your past health problems more schools didn't take a chance on you given this fact alone.

Don't you think it's overkill though? you got into a bunch of places OP would presumably like to go with a similar profile as OP currently has (i.e. without it).

I think you're wasting your time to take the Math GRE for MS admissions, unless you think you want to do a PhD later and will remember more in a couple of months than in a couple of years. It's just a lot of review for someone who took computational level calculus years ago. It's also pretty hard to get a good score, because most people who take it are applying to math PhD programs (I know this doesn't seem align with my previous sentence haha) . That said, it would be impressive if you did well. I just think there are better uses of your time. I'd apply to a range of places, but definitely take a couple swings at the top places (Stanford, Berkeley, Chicago). I'd be pretty surprised if schools ranked around 20 rejected you. Keep in mind what you want out of this degree, as it will inform specific school choices. If you look at previous posts I've made similar to this one, you'll get a rundown of what I mean by this.

Yeah, I got one a couple weeks ago

I think almost everyone on here will agree that it's not going to help you get into PhD programs