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  1. I think you can be a bit more aggressive in picking schools. If you're interested in US schools, I'd throw in an application at some top places that interest you (maybe Berkeley/UW/CMU). I wouldn't expect you to get into those places, but wouldn't be completely shocked either.
  2. Being in state makes you cheaper for only one year (not the whole degree) vs out of state (~$10-20k difference), so it may help a bit, but not a ton
  3. Being both domestic and URM are big factors in admissions. I'd ballpark being domestic increases your acceptance rate by ~2-3x. URM is harder to say concretely, but is definitely a substantive, positive factor.
  4. This is bad advice. It's very unlikely an extra year would get you into Stanford (without blowing my anonymity, I can say this with high-confidence) Berkeley/Stanford level schools will be somewhere between very unlikely and impossible (the fact you're international makes this much harder, unfortunately). I don't know as much about less competitive schools, but you are fairly strong, and I wouldn't be surprised if you got into some schools in the 5-15 range. I wouldn't suggest taking a gap year, unless maybe you had something exceptionally cool to do for that year. COVID or not, life goes on... I'd focus all your time on your research between now and application deadlines, that's what is likely to make the biggest difference.
  5. I'd also add that many masters programs aren't really a "PhD-preview", but more of an extra year/two of undergrad, in that they are filled with coursework. You have plenty of math, don't worry about it. Same for programming. Having a paper is nice, but plenty of people get into top stat programs without them. If your professors says nice things about you that's what really matters. I don't want to start a fight here, but I don't think this is true, or the best advice. E.g. at Berkeley, I don't think they've accepted any Berkeley masters students into the stat PhD program (1 or 2 may have gotten into biostat), out of the 40+ masters students per year. I may be wrong, but I would be very surprised if, in the past five years, Stanford has accepted more than 1 student out of their masters (out of maybe 100-200 masters students in those 5 years), and my guess would be they haven't taken a single one. Regardless, I would encourage anyone (OP or future people reading) to thoroughly vet claims like this before you use them as part of a big life decision. While there are some exceptions, the standard path in statistics is, by and large, to go straight to a PhD from college. Especially for domestic students. For CS it is a bit less uncommon to take time off, but (for applied ML folks at least), the more common approach is a AI residency at big tech cos (Google, FB, etc) rather than taking a bunch of courses in a masters.
  6. I would just apply for a PhD if I were you, you've got plenty of research experience, especially if you do indeed take+do well in the Berkeley PhD core courses 205A/B, 215A/B. Sounds like you'd have a shot at the (stats) PhD programs for those schools (Stanford may be a stretch), so getting in for a MS shouldn't be a problem. I'd really just talk to the PhD students/professors you've been working with - they'll know how strong of a letter they will write for you, which noone else does.
  7. I'm a Berkeley grad, but I won't reiterate the pros that have already been mentioned (size/quality of ML profs/postdocs, overall university quality, higher ranking). A few points: You're worried that "you make a commitment early in the program as to your research area". Functionally, you're expected to find an advisor by the end of your second year (some people do take longer, but not recommended). Idk how CMU works, but 2 years is typically enough to explore. Some people commit as early as first semester if they want. Berkeley is more expensive than Pittsburgh, but it's also an otherwise awesome place to live. Sunny, not too hot/cold, beautiful nature, spitting distance from SF, wine country, Yosemite, Big Sur. Plus fresh produce. I always hear that Pittsburgh is "nicer than you think", but still...
  8. In top 10 programs, I'd ballpark that ~10-15% of people drop out, so it is uncommon but by no means unheard of. PhD's aren't for everyone, and people get that. Basically, if you're not happy and don't think that will change you should probably drop out. Otherwise, you'll end up in your late 20s, poor, with a mediocre PhD (if you don't enjoy it, it won't be great), and a ton of residual stress/anxiety to work through. A few caveats - If you are far enough along - say 1, maybe 2, years from graduating, there may be an argument for gutting it out - there is a tangible benefit to graduating. - If you don't get a PhD, you won't work in academia, so I wouldn't worry about letters of rec (side note - you should have a frank conversation about this with your advisor if you haven't already) - If at all possible, you should do the work to get a masters. If you've stuck around for a year or so, I think most schools will give you one without too much work (maybe a couple extra courses).
  9. I graduated from Berkeley stats PhD - the courses are rigorous, but not crazy. I haven't really heard of PhD students dropping classes because they couldn't handle it. We do have a pretty laid back set of requirements - no written qualifying exams, only an oral exam you take sometime between your second and fifth year which students never fail. Anecdotally, I've heard Gelman is very difficult to work with (a Columbia PhD student volunteered that on my visit day) Berkeley is really great, but I wouldn't stress too much - you can get a great education at any of those schools. Just find somewhere that you'll be happy!
  10. I know of people who have gotten in off the waitlist in the past, so it does happen (unlike other schools, which seldom use their waitlist). FYI, people regularly turn down Stanford. I've heard that students admitted to both Berkeley and Stanford tend to split around 50-50.
  11. I think it's fine to reach out to whoever, 2 caveats: - To avoid wasting people's time, wait until you're accepted (you may be great, but admissions is random) - Keep your email brief, and if they don't respond (a likely outcome), leave them alone
  12. I don't think it matters what their degree is in. Especially if you're doing ML type work, practically the gap between a CS/applied stat/ML PhD can be very small/non-existent.
  13. If you were sick, had a death in the family, or a reason like that, mention if off-hand in <= one sentence. Otherwise, don't bother.
  14. Also "otherwise qualified". If someone were to fail, say half their classes due to an illness, they're not otherwise qualified, and would be rejected. FWIW, Gauss is basically a troll, so this will be my only post.
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