Robbentheking
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Posts posted by Robbentheking
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13 hours ago, dberlind said:
Anyone have an idea what the odds of getting off Chicago's waitlist are like?
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.
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1 hour ago, BL250604 said:
I wouldn't exactly say this is the case. You get paid a living wage to work very hard and grapple with complex ideas. Reading wiki, while sometimes is a supplement, is certainly not the main activity of a Ph.D. candidate in Statistics.
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.
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4 minutes ago, bayessays said:
He did not ask whether he should go back to school for a decade to get CS pre-reqs and then apply to CS PhD programs.
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.
13 minutes ago, bayessays said:This is a post about getting a PhD in statistics in a statistics forum from an OP who has a MS in statistics.
'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.
10 minutes ago, bayessays said:He can take 5 minutes out of his day to study the logistic regression Wikipedia at either his current job or his PhD, so I have no idea what point you're trying to make here.
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.
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25 minutes ago, bayessays said:
It may be true that OP could enjoy their job more if they understood what they're doing better - but a PhD doesn't accomplish this goal. They have already taken all the relevant coursework. They are equipped to read Wikipedia. OP specifically mentioned things like NLP/deep learning which are not even topics covered in statistics departments.
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.
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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.
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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.
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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
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I would definitely reply. 'Thanks for the good news. Hope to talk more soon' or something like that.
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On 5/23/2017 at 5:34 PM, BatsuGame said:
So, you believe the rest of my profile is strong enough that retaking the test is worth it?
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.
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10 hours ago, phieza said:– 90th–95th percentiles on Putnam Competition in freshman and sophomore years.
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.
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2 hours ago, Innominate said:
I'm going to offer a different take than robben did on the subject test: Taking the Math GRE and doing well will help you (of course!), and I can't see any reason that reviewing calculus is not in your best interest. You don't have to send it if it goes badly, so why not give it a shot? If you have to choose between that and getting good grades, then get good grades.
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).
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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.
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7 hours ago, msnotmrs said:
Has anyone gotten an acceptance to UW-Madison's MS stats program? It looks like some people have reported rejections, but no acceptances
Yeah, I got one a couple weeks ago
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I think almost everyone on here will agree that it's not going to help you get into PhD programs
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56 minutes ago, machinescholar said:
This is one of the most prevalent myth on Wall Street. Perhaps, NYU MathFin AdCom may give another take on the same topic:
**Also note that while the author at quantstart offered some interesting ideas, he seems (at least from his profile) to never work in a Quant desk before.
Not saying this is bs per se, but of course finmath department at NYU is going to say that, just from a marketing perspective.
4 hours ago, ECE23 said:What I meant to say was. I have not personally invested myself enough into mathematics to find out what my full potential actually is, due to other obligations and distractions. Everyone who is a "beast" in their field has invested the majority of their time into their respective subject for years, without exception(if you know of an exception I'd be curious to hear about it). Whether or not I have the aptitude to reach that level remains to be unseen because I have not been committed to the study of mathematics.
For sure. Didn't mean to come on too strong.
Certainly in math I think it's near impossible to get to the top of a subfield without devoting your life to it. Anecdotally, I had a professor in undergrad that told me that he was spending 24 hours/week on each math course he took by the time he was a senior at Harvard. This guy was a seriously smart guy, had that level of commitment, and ended up struggling like everyone else in math to get a professorship.
You likely know this given your interest in finance, but check out https://en.wikipedia.org/wiki/Michael_Burry if you haven't. Cool example of a smart guy dabbling in something at a high level.
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2 hours ago, ECE23 said:
basically took 2 years off from pure math after I got my internship at Chevron. One month ago I started again and I'm already deep into Mendelson's Introduction to Topology, which I am currently reading mainly due to interest and partially as a bid to raise my mathematical maturity. The book covers metric space, topological spaces, compactness, homotopy, the fundamental group, etc. Many of these topics are fundamental to Real Analysis and overlap. I have been studying several hours almost every day in addition to my full time job. I will finish the entire book in several months after which I plan on working through Rudin's Introduction to Mathematical Analysis, start to finish, just to give myself a very solid background in analysis for starting graduate school and to learn the material covered in a second Introductory Real Analysis course.
This sounds good, especially the drive to self study, although the deeper theorems in the Topology book are probably not super relevant to the courses you'd be taking as a stats grad. You probably be better off just mastering Rudin, if you can stomach it. Definitely work to improve the GRE score, and maybe take the math GRE too if you want to show off your ability.
2 hours ago, ECE23 said:The point is that I am not a beast in my field because I had too many other things on my plate such as an extremely time consuming engineering degree and internships.
This rubs me the wrong way a bit though. Seems like quite the assumption imo...
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Well, my general impression of quantitative finance (disclaimer: I have't worked in it), is that if you want to just jump from theoretical math/statistics to getting hired, you need to be a beast at your subfield. Otherwise, I think it's much better to be able to get shit done (read: be good at programming).
What is the approximate rank of your undergrad institution? what textbooks did you use for analysis/algebra? what did you cover? I agree that you seem to be better suited to statistics departments than CS departments, but just know that there will be people with stronger math backgrounds as you applying, especially at somewhere like Chicago.
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1 hour ago, Cioran said:
Additionally, I lived in Philadelphia for about two years and attended classes a few classes at Penn. It may be a personal preference, but I absolutely hated the city.
I can't comment on the programs, but I grew up in Philly. I think the city is great personally. Great mix of old and new. Many good restaurants. Great art museum. Access to outdoors with Fairmount park/east river drive. If you are willing to live within 15 min of campus, there's a diversity of neighborhoods to choose from that (I think) should be pretty affordable. I'd imagine most Penn grad students live in West Philly, which isn't the nicest area for sure, but that's really not a must if you're wiling to take a bus.
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I'd ask quantnet this same question.
How much math have you had at this point? I'd think for most of the top MFE programs you need at minimum the undergrad calc sequence, linear algebra, maybe a calc-based probability course, and some ability in a programming language.
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23 minutes ago, lynntoujours said:
You can try Columbia's MA Statistics Program (ranked 20ish I believe). No kidding, but their deadline is in April!
Good shout, but I have heard some not so great things about the program. OP: If you search around these forums, there are a couple of threads you should read
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3 hours ago, marmle said:
Also there was a Michigan stats rejection posted by a domestic student yesterday (think that was the first). I wish they'd just send all of the decisions out already lol
What even is this process? Seems like a strange way of tackling 300+ applicants
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5 minutes ago, marmle said:
Yeah and a second michigan acceptance just got posted :/ I wish more people would write a little something in the results search (personalized email, email to check website, etc.) so the rest of us would know whether or not to expect to hear anything (personal emails probably get staggered, emails to check websitea probably go out at once, etc.)
I'm totally with you on that.
If you look back a Michigan results last year, the acceptances seemed not to all come at once, assuming we can trust people to report this kind of data correctly.
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1 hour ago, poopyhead said:
Looking at the Survey makes me wish I applied to CMU Stats/ML, CU Boulder CS, UMD AMSC, and Cornell ORIE. Why didn't I apply to more programs???
looks like we have a cheeky michigan acceptance too..
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39 minutes ago, machinescholar said:
Yes, Harvard 1 year duration and no thesis requirement are my biggest concerns. Also, at least from the past projects which I worked on, Theoretical Machine Learning is, in my opinion, more closely related to Maths and (Theoretical) Stats than CS.
Obviously you're not doing a PhD (yet), but maybe glancing at the actual work that faculty are doing wouldn't be a bad idea. All the schools you mentioned have insane math departments, so you're not going to get much insight by looking at it on that level.
Fall 2020 Statistics Applicant Thread
in Mathematics and Statistics
Posted
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.