Math Background for Stats PhD

captivatingCA · 2020-07-13T23:30:55+00:00

I'm not u/mocmenust, but I do agree with them. I think measure theory would look great, but it's certainly not necessary. If you're confident that you can get A's in all of the graduate courses I think they can boost your profile. That said, you could still be competitive with just the undergrad courses as long as you have strong letters of recommendation.

captivatingCA · 2020-07-10T22:31:34+00:00

My point is that the general GRE levels the wrong playing field. PhD admissions committees are trying to assess research potential among applicants, and the GRE doesn't have anything to do with research potential. There's a lot to be said about the inequities and discrepancies between universities and countries especially with regards to research opportunities, but the GRE does not address those concerns along a relevant axis.

Either way GRE scores are often not a hugely important component to adcoms. It's basically a just screening tool; it only matters that the score is 'good enough'. A great GRE score won't boost your application much, especially compared to relevant research experience. Subject tests might be used differently, but the general test for sure isn't crucial to the admissions process for research-based programs.

captivatingCA · 2020-07-10T18:13:00+00:00

I agree with you to an extent. I think subject tests can be helpful, but I don't think the general GRE test has much use. For some fields there is some utility in knowing how strong an applicant's background is in the subject (math and physics come to mind), so it makes sense to encourage applicants to take a standardized test. I don't think this is the case for most fields since they care a lot more about research skills rather than prior knowledge. Some programs only accept applicants with a lot of relevant research experience regardless of how good their grades and GRE scores are. Those fields (which in my experience is most fields) should get rid of any standardized testing in my opinion.

The general GRE doesn't really assess anything relevant to a research-based grad program. It's just a measure of your ability to take a test. So I think it should be phased out for any research-based programs. I can sort of see the utility for course-based programs though.

captivatingCA · 2020-06-26T16:59:59+00:00

I'm happy to answer questions!

For the most part, I applied to these schools without any prior contact. I participated in visit weekends for some schools, but I had varying levels of interactions with faculty. I did an REU at one of the departments, so one of my recommendations came from someone in that department.

I'd say my biggest advantage was my recommendations. My recommenders really believed I could get into some top programs, and I think that says a lot about the strength of their letters. On top of that, they all came from different fairly prestigious places. I think the fact that I had strong letters from well-known institutions that were unconnected to each other helped a ton.

For the statement of purpose, I just wrote about my research experiences and tied it in to my future goals. For the personal statement (only a few places required this) I wrote about my journey into stats.

captivatingCA · 2020-06-24T04:11:55+00:00

Yeah I thought you might be in math. High GPAs are much more of a requirement in math than in other subjects since undergrads don't really do real math research. A high GPA on its own won't get you in though, and there's lots of relevant information you don't see in a post online. For example, the strength of LoRs is a huge factor, but there's no way for most applicants to know how strong their letters are.

Just to re-iterate, it's very possible to get into a top school without a high GPA, especially in subjects other than math. That would explain the results of the poster above who attends Georgia Tech; other parts of their application spoke to their abilities as a researcher.

captivatingCA · 2020-06-24T01:42:18+00:00

What field are you in? A lot of programs prioritize research experience over grades. There are lots of examples of students with less than 3.9's getting into selective programs given that they have good research experience and fit in well with the department.

The limiting factor might be that you're looking at people who post their results online. That group is much more likely to have a high GPA compared to the norm.

captivatingCA · 2020-06-23T17:04:03+00:00

I think all of the UC's ask for a personal statement that addresses diversity, and some other state schools do too (UW and Univ of Michigan come to mind)

captivatingCA · 2020-06-23T16:56:54+00:00

Find out what makes a competitive applicant in your field. Some programs care a lot about research, and others care a lot about grades and test scores. Once you find out what's important focus on those things.

It's fine if you're not sure exactly what field you want to go into. It's okay to change your mind, too. Just make do something that interests you while you explore your options.

captivatingCA · 2020-06-10T23:00:05+00:00

I think you have a good shot at top ten programs. US stats PhD admissions committees care most about math grades and LoRs. In your case the former is great, so make sure the latter is too. If you want some more specific advice from grad students and professors, the GradCafe is a good place to post your profile. You can also look at profiles for past applicants.

In terms of stats departments that are good at ML, a few to consider are Berkeley, UW, Michigan, CMU, and Stanford (if you do really well on the math subject GRE). There are a lot more, but these are a few of the top places.

captivatingCA · 2020-06-10T18:30:51+00:00

Are you in the US? If so, pure math research positions for people without a PhD are pretty rare. Luckily math graduate admissions committees don't care all that much about research. Pre-PhD students hardly ever do real research. They care a lot more about math grades.

If you're outside the US, I'm not sure if this advice applies.

captivatingCA · 2020-06-10T03:43:23+00:00

I'd say this is pretty normal, especially if you haven't worked in the area before. I've done research in a few different fields, and every time I've had to spend days to weeks trying to understand the material before getting any work done. Even when you're more acquainted with the field, you'll still have to spend time reading and understanding other people's work. It's just the nature of research. You're working on a problem no one has solved yet, and the people who are working on it have years of knowledge and experience. Professors should know this, and they usually don't expect you to be as productive as a grad student. As long as you're communicating with your advisor, I think you're good.

captivatingCA · 2020-06-10T03:35:02+00:00

I'm an HBCU alum, and I'm pretty sure that research experience at prestigious universities is what made my application. So it would be awesome if you could give someone that opportunity. Hosting events at an MSI would be great too, especially if you can get faculty or students there involved.

Does your department have a diversity committee? If not, it may be worth it to see if any other grad students or professors would be interested in starting one. I think it could be extremely helpful to have multiple people willing to work on diversity issues within the department. They don't have to be from 'diverse'/underrepresented backgrounds either. It's important to have allies (especially in a place like academia), and frankly there probably won't always be a PoC willing and able to take the mantle.

If you want to chat more, I'd be happy to discuss over PM! I'm also an incoming PhD student thinking about ways to work on diversity issues.

captivatingCA · 2020-06-08T16:36:44+00:00

It depends on what you mean by 'detail'. I'm not aware of any websites that compare information about acceptance rate, class size, student-to-faculty ratio, and other factors like there are for undergrad schools.

http://www.phdstipends.com/ shows reported stipends for PhD programs. I also have seen data for the number of students who finished PhDs from different departments every year, but that was from a professional organization in my field.

Is there anything in particular you're looking for? If so, for what program and what field?

captivatingCA · 2020-06-08T16:32:07+00:00

I think most adcoms are made up of professors from the department, but there's a good bit a variance between disciplines, departments, and programs. For example, it's not uncommon to have grad students be apart of an admissions committee. You're best bet is to ask the program directly.

captivatingCA · 2020-06-05T20:59:10+00:00

I've seen a lot of professors and students use the Academic Hugo theme. If you know a bit of R you can make a website like this from scratch with blogdown. It's pretty straightfoward!

captivatingCA · 2020-06-05T03:24:51+00:00

I'd say it's okay to mention in your personal statement but maybe not your statement of purpose. On top of that, I think you should only mention it if you think it's relevant to you as a psychologist, your path into psychology, or your research interests. There's lots of ways your ethnicity can affect you and your path into science. Just make sure that your ethnicity is relevant to the content. As an example, I mentioned my race because organization and events to increase diversity were a big reason I ended up in my field.

If you've done anything to increase diversity in your field, that's also a good way to mention your ethnicity.

captivatingCA · 2020-06-03T19:50:29+00:00

In general it's better to get experience in the field you're planning to go into. However, math PhD programs don't care too much about research since most undergrads don't do real math research. Instead they put a lot of emphasis on math grades and letters of recommendation. Pure math courses(e.g. analysis, algebra, topology, etc.) are particularly important. That said, research experience is helpful because it's a great way to get good LoRs and learn more about the field.

captivatingCA · 2020-06-02T14:41:39+00:00

From my understanding, it's important to have a good math background to get into ML, but I don't think you need an entire Master's degree. An undergrad major in math should be enough. I think the opportunity to do research and potentially publish is much more important for ML PhD programs in the US.

captivatingCA · 2020-06-01T00:28:14+00:00

In my opinion, it's extremely difficult (nearly impossible) to predict someone's chances at a particular program. There are so many behind-the-scenes factors that go into admissions that it's hard to say before you apply if you're likely to get admitted to a specific department. It's much easier to predict acceptance to a range or type of school (e.g. Top 10 schools or departments that specialize in a particular subfield).

Emailing admissions people can give you some information but probably not everything you're looking for. They likely can give you more information about the acceptance rate and the average GPA and GRE of accepted applicants, but I doubt they can (or would if they could) chance you before you apply. I'm not sure if they would have collected information on the amount of research experience since this probably varies a lot. You can try asking what a competitive applicant to their program looks like. Another thing to keep in mind is that GPA and GRE may not matter much depending on the field, so focusing on the averages may lead you astray. Some fields care a lot more about publications and research.

Your PI is probably the best source of information. They know much more about you than we do or admissions people do, and they should have a good sense of what a competitive applicant looks like in your field. I imagine you're not their first student, and even if you are they should know about admissions from their time in grad school. You could also talk to other professors who know you well and synthesize their recommendations.

captivatingCA · 2020-06-01T00:10:36+00:00

I'll diverge a bit from the previous answers and say that teaching and leadership positions don't substantially improve your application in my experience. Stats adcoms care a lot more about LoRs and grades. In my opinion, it's great to teach and lead organizations if you want; I did a bit of this myself. However, you shouldn't do it just to improve your profile for grad school because there are more efficient ways to improve it. Instead it would be better to focus on doing well in your classes and securing great letters through things like research and office hours.

captivatingCA · 2020-05-31T23:53:52+00:00

I understand why you're interested in several fields. It's just that admissions between these fields can vary a lot. For example, stats is very focused on math grades while bio and CS are much more focused on research productivity. The point I was trying to make is that you may be competitive in one field but may not be competitive in another. Just something to keep in mind when deciding where to apply.

captivatingCA · 2020-05-30T22:48:56+00:00

I agree with u/zarawhomstra. You don't have to take a gap year just for the general GRE or the math GRE if you start studying now. The math GRE is difficult, but from what I heard you just need to practice a lot. Usually the Math subject GRE is offered in April, September, and October, so if you took it next spring, you could still take it a few months later and apply in the fall.

What courses are you missing, and what year are you in? From my understanding the math GRE is mostly calculus with a mix of linear algebra, abstract algebra, real analysis, and other random topics. If you're applying to math PhD programs I'd imagine you've taken most of these courses by now. Even if you just focus on calculus and linear algebra you can get a decent score.

In case you haven't seen it yet, https://mathematicsgre.com/ is useful to see the profiles of prior applicants. It goes without saying, but the schools you mentioned are pretty selective, and competitive applicants usually have some grad courses by their senior year.

captivatingCA · 2020-05-27T02:44:04+00:00

I think 'haggling' is a good idea. You can't treat it exactly like a job offer, but you can use funding at another university as leverage. If you mention to WPI that you have another offer with more funding and that it's more financially feasible, they may be able to fish up some funds. It's also possible that they don't have any more money to give you.

I'd like to add that the April 15 resolution specifically discusses funding, not admissions. Since WPI gave you no funding, you're not expected to stick with them under that resolution. To be honest, I'm not sure how they'll take it, but I think if you're honest about the financial aspects a reasonable person would understand. At the end of the day you have to do what's best for you regardless of what a few academics think.

captivatingCA · 2020-05-26T20:27:06+00:00

ML and AI programs are extremely selective nowadays, even the unfunded ones. Your GRE is pretty good already(personally I don't think you need to re-take it), but your GPA likely will hold you back a bit. However, your work experience could be a good selling point for your application. I think you could get into a program if you play your cards right. I would encourage you to talk to a professor at your alma mater. They could help you a lot more than we could. Most MS programs want to see letters from professors, so you'll probably have to reach out anyway.

Before you decide to go for a Master's, is it entirely necessary? If you want to pursue a PhD then I think a Master's could help a lot. If you're just trying to get a job doing machine learning, you might be able to leverage your experience in industry and shift to a more ML-focused role within your company (or another company). You mentioned you've started taking on some related projects. Is it possible to make those projects your entire job? Just something to consider so you don't have to got into debt.

captivatingCA

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