Robbentheking

I've done a good amount of research on masters programs. It seemed to me like Chicago was the best for PhD preparation in the country, hands down. I think Harvard and Stanford may be better for industry, both based on name recognition and the focus of the programs. Stanford I recall labels their program as a 'terminal masters' and specifically stresses that it is rare for masters students to obtain admission to the PhD program. Chicago seemed a lot more flexible/theory orientated. They've also taken a couple kids from the masters program as PhD candidates the past few years. Just a couple of data points. I think Harvard was only a year long program? That probably isn't too helpful for you, as won't you application won't have substantially changed by next fall. Think about recommendations...you can't expect someone to write you a great rec after being in their class for 2 months. To be honest though, I don't know anything about theoretical machine learning. Maybe you should be in a certain place just based on that interest. If it's going to be CS heavy, maybe you should be looking at school with a good CS department as well? Chicago doesn't really fit the bill there, as far as I know.

Dude I know. Maybe more applications than before? Hoping that's not the case

seems like Washington is really the only school to get completely through the process just looking at the results search

Well it depends on what a competitive score is for you, where you are now, how much will power you have, and how much time you have. If you were bad at math in high school, you probably have some work cut out for you. Just practice practice practice. There's tons of advice on this forum and elsewhere, but the biggest key is to figure out how to make math practice not feel like a chore. The best mathematicians in the world do math because it's fun for them. They would never be where they were if they dreaded sitting down to do math. Think of the quant section as a puzzle solving section. For the verbal, you should be okay if you read a fair amount already. But as another user mentioned, I found that making flash cards on my phone of the strange vocab words and just studying them whenever I was on the bus or had an odd few minutes really helped get a few extra points out.

The math on the GRE is definitely learnable, but certainly someone who hasn't had to engage in this type of thinking in decades would have to study much longer to master the material.

Granted the math example is not typical, but there's obviously some correlation. As you noted above, the verbal section sucks, but it doesn't suck to the degree that there are tons of people getting 140s who could walk into the best history departments in the country and be stars from day one. The question is whether the level of correlation is acceptable, and the answer varies from program to program. What you're saying makes sense to me if you are in a field where the correlation is low, but then you should also be pointing fingers at the adcoms. I've read some crazy stuff about how little professors know about the test. That seems like as big of a problem as the test itself.

I think this is definitely worth talking about, but I don't think it's this is easily remedied. Maybe you know more about this type of thing, but it doesn't seem trivial to me to come up with a test that reflects pure learning potential and cannot be studied for. I suspect that the main problems for older test takers are not being around the material for years and not having time to prepare. It's also worth noting that in some cases, the learned knowledge is, if not directly important, highly correlated with important skills. For example, in mathematics/statistics, if you want to go to a top program and can't get near a 170 on the quant section, there are definitely some red flags that are raised, even though gre math has nothing to do with the math you'll end up doing in a grad program. Also, before you declare the system to be discriminatory, you should really do/find a study about whether or not adcoms really take gre scores at face value, i.e. hold all applicants to the same standards. After some of the reading I've done, I wouldn't be surprised if this were the case, but considering that it's no too hard to read up on the shortcomings of the test, it's something that would have to be verified. Regardless, I wish you all the best. The test is a pain in the ass for us college kids, so I can only imagine how much of challenge it is for you.

I just want to add that I have a friend from China who's told me that the dynamic in China is very different from the US. In his experience, undergrad comes with an insane amount of competition, while grad school isn't really that crazy because most of the smart kids go to America to continue their studies. Those university rankings are based on a lot of factors and I think it's safe to say better university ranking does not imply math undergrads know their material better. Some of these Chinese unis seem like good counterexamples.

But like how far did you go with math? Like the classic calculus sequence and linear algebra? Or did you take some proof based courses too? My buddy said the lowest he'd be comfortable submitting to a top 3 school on a PhD app would be 167/168 quant. He is pretty driven though. And if you still have your finance job, you don't really have much to lose.

That does seem odd to me too. I think the verbal score could actually be useful information even for math programs if it were structured differently. Reading comprehension is an important skill and some of questions are basically logic tests that I'd want all my math/econ/cs grad students to be able to get 95% of the time in a vacuum. The problem is, right now, it's possible to have outstanding reading comprehension/logic skills but get like a 160 just because you didn't take the time to cram 500 words into your short term memory, or conversely, to get like 165 with inferior verbal skills and good short term memory. As for your score, I'm just guessing here, but as you say, 85th percentile doesn't seem disastrous at all. Honestly though, I would expect it to be one of the lowest scores an accepted student at a place like MIT would get. I'll text my buddy who I referred to earlier. What does your math history look like? That would definitely help contextualize your score.

I have a buddy who was considering apply for Econ programs, but decided to do an extra semester so he could take a few more math classes and get a math major. Not sure of the emphasis on the GRE, but my understanding is that Econ programs like to see math aptitude, even if at the end of the day you won't be needing to know about abstract algebra.

I just want to add that just because professors have left your old uni, it doesn't mean you can't ask them. Professors are easy to track down because almost all maintain personal websites.

@footballman2399 does anyone in stats really care at all about complex analysis? I could imagine some of the techniques for integration might pop up in some proof somewhere, but otherwise it doesn't seem too applicable.

I'm just an applicant as well, but my impression from reading through these forums is that for someone applying to masters programs, your profile is quite competitive. I guess having Real Analysis on your transcript, or any sort of proof based math, would be ideal, but your more interested in applied statistics anyway. My impression is that 168Q is more than sufficient for master programs. I wouldn't worry about that. Obviously you've basically picked all the best programs here, but I'd like to think you'll find success somewhere on the list. I think I read somewhere that Columbia's MS really isn't hard to get into. As always, it would be cool if one of the people that actually knows what they're talking about would pipe up. I think in general there are a lot more profile evlauations for PhD on here, making it a bit harder for MS applicants to get a handle on where they stand.

Post in the math/stats forum. They know way more about biostats specifically. did you take the TOEFL?

next time don't study so much right before the test. I took like 5 practice tests in my prep and noticed that the single most important factor in determining my performance was being rested and alert

@arima thank you so much! this is all really helpful

Thanks for the ideas. I hadn't looked at the masters programs at either of those departments yet. I should have done more research before posting. I had just looked at master programs at some of the top departments and was kind of surprised the orientation was so professional

Well idk really. I sort of hate the phrasing I used here now that I read it again. I don't mean to insinuate that Michigan for example is 'any old offer,' as it seems to be a very strong department with many people much smarter than me. What I'm trying to get at is I'm not just going to take a PhD offer for the sake of taking one, especially if I can get into a really good masters program and fill some of the holes in my profile in the next couple years. To be honest, I don't really know if the programs I mentioned would put me in a relatively tough spot in terms of academic placement or what the cutoff is for 'any old offer' is; it's sort of all part of my question. I've done a bit of research by just randomly looking at younger faculty profiles at schools and it would be wrong to say that all of the faculty come from top 5 programs. That being said, places like Stanford and Berkeley pop up quite a lot, especially in say the top 15 departments. 'Cornering out' is a strong phrase and again was probably poor word choice, but going to a top department seems like the path of least resistance, unless people outside of this top tier are just not as interested in academic careers on average. This is also coming from a bit of reading I've done on these forums. I like to think that if you worked with really great faculty at a second tier department and produce good research you shouldn't have too much trouble getting a job, but who knows.

Hi guys, I've been reading through these forums for the past couple months in order to get a feel for the admissions process etc. and have learned a lot, but I guess it'd be nice to have a bit of input on my personal situation. I'm a senior studying math and am interested in theoretical statistics and probability theory. It's pretty important to me that I keep the door to academia very much open and I've read that academic placement can get really hard outside of the top tier. With that in mind, I wonder if my best option would be to focus largely on applying to masters programs to improve my profile. The issue with this that I find is that, although I haven't done exhaustive research, it seems most masters programs are very much professionally oriented, which really isn't what I'm looking for. The only ones that I have found that I really like are Chicago and Harvard, which I guess are possibilities for me, but are very competitive obviously. Anyway, I'll put my profile and current ideas for schools below, and would be curious to hear any input/advice anyone has to give, especially from any faculty. Thanks! Undergrad: Ivy Majors: Mathematics, German GPA: 3.88 overall, 3.90 Math, 3.87 German Honors/ Awards: classic bs like dean's list, a few German department awards. (I actually got "Highest Honors" in my German major for an A on my senior thesis, for whatever that's worth) Type of student: domestic male GRE: Verbal 170, Quantitative 167, Writing 4.5 Math GRE: am not taking it... just didn't have the time to prepare for the regular gre, work full time, and review all that stuff well enough to expect a good score. Relevant Courses: Integral Calc (A+), Multi Variable (A), Linear Algebra (A+), Intro to Proofs (A), Abstract Algebra I (A-), Real Analysis I (A), Abstract Algebra II (A), Real Analysis II (A), Calc. Based Probability (A+), Intro to PDEs (A+), Complex Analysis (A), Topology (grad course) (A-). Research: None in math or statistics. I have a 40 page senior thesis in german and currently am doing an extended internship in research and development at an electronics firm, but it's largely physics based with a smattering of calculus involved. I don't think either of these will help me too much. Letters: -analysis professor who I had for two semesters -algebra professor who I had for two semesters -topology professor first two should be good because they both know me and what i can and can't do very well. third is probably kind of meh Worries: I think they're obvious: 1) Lack of research, and the reliance on professors I only took classes with for letters that comes with this 2) no math gre pretty much eliminates me from top tier PhD if my lack of research didn't already Thinking of applying: Masters: Chicago (first choice), Harvard, .... (any suggestions for non-professionally oriented masters that aren't so competitive? I know I have to do more research here) PhD: I guess maybe large departments where I would have research flexibility. I guess I'll apply to places like Michigan, Wisconsin, Minnesota, but again, I'm cautious of cornering myself out of academia by just accepting any old offer.

@PoliticalOrder I haven't really done any research, but from personal experience and word of mouth: The amount of meals doesn't matter insofar as you are getting the same amount of calaories. For me personally though, trying to combine two or even three meals into one huge meal results in me eating less calories per day on average I think. On the flip side, a lot of athletes try to eat throughout the day to get more calories in their system during intense weight training. You just have to pay attention to your body.

@TakeruK Well, I may be deemphaisizing research a bit on some subscious level just as an ego boost, but what I've written above is a pretty decent respresentation of what I've heard in my math department. With regards to the mathematical ceiling, I think it can really have a more dynamic definition. Math can get really hard and no matter who you are, you are going to get to points where you just really need to like math enough to put in the time and grind through the rough patch. The degree to which you are willing to sacrifice for the subject is part of your ceiling I think, and I think most professors would agree to that. Mathematical ceiling is a phrase that is casually thrown around a lot that is actually pretty deep imo. In general, I'm wary of people who fall cleanly on either side of the fixed intelligence vs. growth mindset debate. I think experience shapes all of his greatly on everything from aparent ability to desire to learn something, but the idea that there aren't people with inherent advantages in certain areas doesn't make much sense to me. Forgive me if I sound really stupid because I'm reaching far out of my field, but I'm not sure I understand how humans fit into the evolutionary framework if intelligence is just something we all acquire during our lifetimes.

@TakeruK First off, thank you for taking the time to write this long and clearly well thought out post. While I'm aware of the fact that getting a recommendation from someone who only a taught me in a course is not ideal, I would like to say that especially in math, and to a lesser in statistics, this is not totally uncommon. Certainly in math, no one outside of the true rising stars knows anywhere near enough as an undergraduate participate in meaningful research. In this sense, one of the better measures that grad schools have of future research potential is simply to try and make sure a student is not close to reaching his or her mathematical 'ceiling'. In this sense, professors one has had a course with are really not the worst evaluators. Certainly research need not be meaningful to give an indication about research potential, but I clearly recall going to a prospective math major QandA session when I was a sophomore whereby someone asked about how to get involved in undergrad research. One of the professors on the panel, one who was subsequently fired for his lack of teaching ability but almost immediately picked up by UChicago becasue he was a brilliant researcher, gave the following answer: 'Don't waste your time with research as an undergrad. You just don't know enough. The best thing you can do to prepare for grad school is pick up a text book during the summer and try to do all the problems'. This answer struck me as ridiculous at the time, but other, more level headed professors I've asked about this answer have pretty much agreed. Coming from a math background, my interests in stats are almost totally theoretical and intersect heavily with pure math. I do not have any research experience in this field and while it'd be nice to have some, I'm not killing myself over this, especially because half of me really thinks a masters program would be best for me right now anyway for a bunch of reasons only partially intersecting with research. I've done what can easily be spun as descriptive statistics research in the bit of professional experience I have, but haven't gotten a recommendation from a previous employer because I just don't think that would at all be helpful in evaluating my research potential in the topics I'm interested in. The reason for my concern about asking the topology professor follows largely from my comment about 'mathematical ceiling.' I think the way in which a letter from a professor can be helpful is by giving a vote of approval that the ceiling isn't in sight and that the student has an inquisitive mind and a love for mathematics that takes his or her study to a somewhat extra curricular level, and I'm really not sure doing mediocrely in a class really encourages the professor to give his seal of approval that I will be able to tackle anything thrown at me in the future. You can't push the mathematics further if you don't have a full grasp of the existing knowledge. As for German, I did write a pretty significant senior thesis and could get a recommendation from my advisor. Mostly, I just wanted to include a letter from someone who knows me well through the German department because it's something I spent if not half, a significant part of my time on in undergrad; it's a big part of who I am as a student and I just feel like even though it's totally irrelevant in the fields I'm interested in, I want to put my full self on my applications.

I just want to note from a practical perspective that taking a couple extra courses isn't going to have much effect on your average at this point.

I'm a US international, went to school in the US and will be applying to US schools; I'm just working in Germany currently. I actually intend to ask the head of the German department back home to write a rec for me, but I was thinking of making this a fourth rec. It should actually be a very good rec because she really likes me and has openly pushed for me to get somewhat undeserved department awards in the past, but because I'm applying to a quanitative field, I want to make sure I fill my required recs with people that actually have an understanding of what it takes to do grad level work in a quanitative field. I'm in Berlin. I would consider staying here, but to be honest I sort of miss the US and speaking English all the time. It's just a bit easier haha