kingsdead

I don't remember the dates exactly, but I applied last year and was in a similar situation as you (my scores reached after 12/1) and everything worked out. I emailed the schools I was using SOPHAS to apply to when it became clear that my scores wouldn't reach in time just to make sure and they said it would all be fine, and in the end I was not penalized. So I think you should be fine! Relax a bit, and congrats on finishing those applications.

I think that's a good list (for biostats at least, I don't know as much about stats). I'm confident you'll get into many of the biostats schools. For reference I think your profile is better than mine was and I got into many of the schools on your biostats list. Under normal circumstances I would say your biostat list might be a bit bottom heavy, but given that funding seems a bit more uncertain this year it might be good to have that just in case.

OP, I agree with everything @StatsG0d says, except I don't think it's necessary that you take a gap year. Two years is plenty of time to get in more math classes. Eg perhaps you can take Analysis I/II this year, and 2-3 more next year (more advanced analysis courses, abstract algebra, or numerical analysis). That will be enough for any biostats program and sufficient for most stats programs. Best of luck!

Hey full disclosure; I'm not yet a grad student so I don't know how much you should value what I have to say. But IMO, abstract algebra isn't too important for the subject test. It's never more than a few questions - you can always get >90th percentile by doing well on the other questions. So I definitely wouldn't recommend taking abstract algebra (or number theory) just for the sake of doing well on the subject test. If you have some personal interest in the classes, that's different, but those classes aren't particularly relevant for statistics unless you do something specialized like algebraic statistics. Between the others, it sounds like you could spread them out between fall 2020 and fall 2021. I think you'd get more out of functional analysis if you have a better measure theory background first, but I don't think the ordering is particularly important. Just my $.02!

Undergrad Institution: LAC, considered one of the "top" ones. Major(s): Math GPA: 3.74 Type of Student: Domestic Asian male GRE General Test: Q: 170 (96%) V: 166 (97%) W: 5.0 (92%) GRE Subject Test in Mathematics: M: 820 (81%) Programs Applying: Statistics/Biostatistics PhD programs Research Experience: REU in math after junior year. Resulted in two (very standard undergraduate type) publications. Honors thesis during senior year in number theory. No publications. Research data analyst for ~8 months at the global health department of a university. Work resulted in two conference posters. Awards/Honors/Recognitions: Award for applied math/teaching from my college, graduated with honors from department, standard GPA type stuff but nothing fancy. Pertinent Activities or Jobs: Tutor/TA for Calculus, Topology, Linear Algebra, Partial Differential Equations. Research data analyst for ~8 months at the global health department of a university. Did fairly basic data cleaning and analysis, used a lot of R and SQL. I think that this helped allay fears regarding my poor CS grades. Math tutor (part time) after graduating. Letters of Recommendation: Math professor with whom I did REU research and thesis, math professor who taught measure theoretic probability, PI from data analyst job. Assume that all were solid but not spectacular. Math/Statistics Grades: Math (All A or A+ unless otherwise stated): Multivariable Calculus, Linear Algebra, Discrete Math, Real Analysis, Abstract Algebra (basic groups/rings/fields), Topology, Number Theory, Complex Analysis, Combinatorics, Algebraic Number Theory, Homological Algebra (A-), Differential Geometry, Harmonic Analysis, Representation Theory (A-), Asymptotic Analysis, Commutative Algebra, Measure Theoretic Probability, Partial Differential Equations. Stats: Standard calc-based intro stats course (A-) CS: Intro CS (A-), Data Structures (B-), Algorithms (B+), Theory of Computation (A-) Any Miscellaneous Points that Might Help: Peace Corps Volunteer – taught in a rural school, involved in other projects as well including some HIV/AIDS related programs for youth. Applying to Where: Biostatistics (All acceptances with funding): Harvard - Rejected University of Washington - AcceptedJohns Hopkins - Accepted Minnesota - Accepted UNC - Accepted Berkeley - AcceptedColumbia - Accepted Statistics: Columbia - Rejected Chicago - Waitlisted Post-mortem: There is definitely randomness involved. In my opinion there are folks on this site (e.g. earlier posters on this thread) with stronger applications who did not get into some of the programs I got into. It's tough to say until you apply, so as long as you have some chance, just go for it. I think that my volunteer experience helped make my application stronger, or at least a little more interesting, based on how my interviews went. So if you have a somewhat unusual background or experience, don't be afraid to let that shine in your essays/interviews, as long as you can relate it organically to the rest of your application. I didn't attend any interview events – did all of them online or over the phone instead, and this didn't hurt my applications, so don't lose sleep if you aren't able to attend these sort of things! Seems that a few bad grades, even in related areas such as CS, can be offset by strengths in other areas and evidence that you have shored up those deficiencies (e.g. my bad CS grades being offset by my work experience as a data analyst). That's all I got for now! Thanks everyone for all the help.

Thank you so much for the amazingly in depth answer – that's exactly the kind of thing I was hoping for. I still have yet to make a decision but you have given me a lot more to think about!

Hey all, This forum has been very helpful to me the past year or so. I think this will be my last time asking you all for help. I've been admitted to Washington and Hopkins for a PhD in biostatistics, and while I'm aware of how lucky I am, I'm also feeling anxious about the choice I have to make now. I was hoping you all could help me compare and contrast the two. I have looked but haven't seen any threads comparing these two explicitly. About me: I don't really have fixed research interests. I think I would like to work in global health, but beyond that, it isn't clear what I'd like to do. My background is not in statistics so I know very little about what kind of stats I'd like to research. I'm also undecided about what I'd like to do after graduating, though I think academia would be appealing. Some more details: the money at Washington is around 34k/year. In addition I've received a fellowship from Washington at the ARCS foundation which will give 7.5k, 5k, and 5k in years 1, 2, 3 (as far as I can understand). At JHU, the funding year 1 will be 25.5k plus 6.5 to move in/other expenses. The base funding seems like it will increase slightly years 2 and 3 with the possibility of further funding (5-10k extra per year) Some questions I am hoping for help with: 1. Washington seems to have access to more NGOs, eg Gates, while Hopkins has the stronger public health program. Where do you think options for global health research would be better? 2. It looks to me like Washington has a larger faculty and hence broader research interests, which I think might be good for me given that I don't know what I want to study. Is that accurate/does that make sense? 3. While the funding seems better at Washington, I can't tell where would be better after factoring in living expenses. Although I don't want money to be a large factor in my decision, the past two years have made me more conscious of the (lack of) money in my bank account than before. I also know very little about the ARCS fellowship and can't really tell much about what that would entail so any details would be helpful. 4. If anyone could comment on differences regarding the cultures of the department I'd really appreciate that. Any information contrasting the two in general would be awesome. Thank you everyone for all the help so far. I hope to pay it forward on this forum in the following years as I gain more experience!!

I had an interview with them a week ago. It was really quick, like less than ten minutes, just them checking whether I was still interested in the program and an opportunity to ask a few questions. Then I just got accepted like twenty minutes ago. I was accepted to their Masters program (they don't admit applicants with only bachelors directly to the PhD program I think, so that was expected). They guaranteed funding for one year as a GSI. Interestingly enough the date on the letter they sent me said February 13, so it looks like they waited over a week before sending it to me? So I wonder if they're just being slow about getting them out there. Best of luck!!

Got rejected from Harvard Biostatistics (PhD). Didn't get an interview though so that was expected. Only waiting to hear back from three more schools so hopefully this rollercoaster will be over soon! Best of luck everyone

Got an invitation to Washington's Visit Days in late February (PhD in biostatistics). Apparently they will do two informational interviews in the morning (which will be used to help the committee decide on admissions) and then give attendees more information about the program. They will decide about admission/wait-list by March 6. I'm really surprised because I was under the impression that UW only invited admitted students, not prospective students. Are they changing things this year? Or I wonder if this means that they consider me a borderline candidate and they want to speak with me before accepting or waitlisting me, whereas top applicants will be admitted directly? Wonder if anyone has info on this.

Hopkins biostats PhD. They said they would release decisions late February or early March.

Had a phone call/interview today. They asked me to introduce myself, which led to a few follow up questions, and to describe what I wanted to do in the future. Then I had plenty of time to ask questions of my own. It was very pleasant and casual. All fairly standard and in line with what I'd read it would be like ahead of time. Hope this helps anyone preparing for interviews!

Nope, biostats! Sorry for not specifying

Not who you initially asked, but I got accepted to UNC as well and am a domestic student.

Thanks all three of you for your advice! To follow up a bit with @Geococcyxand @bayessays, my GRE scores are 170Q/167V/5.0W, so I'm not worried about those. Forgot the exact score on the subject test but percentile was 82%... Maybe not good enough (given mediocre gpa) for Stanford, but I'm not planning on applying there anyway cause it's such a Longshot, and biostats programs don't require it anyway as far as I know. GPA was 3.75, definitely on the low end for top schools, but I did well in math classes (all As or A+ with a couple of A-) and also took a lot of math. And I did take a calc based intro stat course. I went to a liberal arts college, though for what it's worth it's considered a good one (think Williams Amherst Swarthmore Pomona etc). Publications were in number theory so not related (though analytic number theory... So I guess we used some analysis). One extra question I have, I see that a lot of fellowships etc talk about commitment to diversity and leadership, would something like Peace Corps service potentially help with that? @Stat PhD Now Postdoc, thank you for posting those two links, very helpful. I have been out of school for a while so I will definitely review calculus, linear algebra, real analysis, and hopefully some statistical computing as well like R. Anyway, thanks y'all, and this forum in general, for answering my questions and being a great resource. I will definitely keep everyone posted about where I end up applying to and the results when the time comes.

Hi everyone, I graduated in 2017 and am planning on applying for PhD programs in statistics and biostatistics this year, for admission during fall 2020. I was just wondering if anyone has a sense of what I can do between now and when I apply to boost my chances for getting into top programs. Would appreciate any advice at all! A bit about me: I have a decent math background (real analysis, measure theoretic probability, other upper level undergrad/intro grad level courses in analysis and algebra that are probably not very relevant to stats), mediocre CS background (a few courses where I haven't done too great), spent time after graduating working as a data analyst for a public health program, have a couple of math publications from an REU, and currently am in a volunteering program abroad. I'm done with the GRE + GRE subject test and am comfortable with the scores. I'm just wondering whether there's anything I could be doing right now to help my chances. Some more concrete questions: 1) I don't know much about stats (my background in school was very much pure math). In particular, I have no clue about potential research interests. What's a good way to go about learning more about potential research interests? How important is it to have informed research interests during application season? 2) Related to the first question, would it be worth spending time learning more stats before applying? I'm wondering about something like going through Casella Berger or other stats books to make up for the fact that I don't know much beyond a stats 101 type course. Ideally I'd take courses at a local university (I've read people suggesting similar things on this forum) but that's not an option for me given the fact that I'm living in a very rural part of the world right now, and will be here until summer of 2020, right before I hope to start school. Would schools care about me taking the time to go through such books? I'm probably going to do so regardless just because I want to learn more but I'm curious how schools would perceive it. 3) As I mentioned I didn't do too well in a couple of CS courses I took in college (B-, B+, etc). I posted about this a while back and some people commented that my experience programming as a data analyst should be enough to offset any potential concerns there. Would it be worth taking some courses on something like Coursera to show schools that I'm serious about improving as a programmer? Would they care at all about that? Thank you all for listening!

Thanks everyone for the advice! @insert_name_here, huh, could have sworn I read that something about Washington being known for theory somewhere on this site, but thanks for the info!

Hi, as the title indicates, I'm curious about the best way to determine the research strengths of a given department. Some are fairly obvious, e.g. Duke and Bayesian, but with others it's hard for me to tell. E.g. I've heard things about how Washington has a very strong theoretical bent, but how would you know that just by looking at Washington's department website? I don't really know any statistics professors to ask about this, which is how I suspect most students get a sense of research strengths and where to apply to. Any advice on how to figure these sort of things out? For what it's worth, I'm interested mostly in biostatistics, and just want to get a sense of what the different departments specialize in so I can begin forming a list of schools to apply to.

Thank you for the help! I was worried it would hurt me for showing lack of focus or something

Question about applications. I have received mediocre CS grades (A-, B-, A- in intro programming, data structures, and theory of computation respectively) and am wondering how much it would hurt my application for biostatistics PhD programs. For what it's worth, I have a solid math background, along with strong GRE and GRE subject test scores, and since graduating I worked as a data analyst for research where I did work with R, Python, and SQL, and my PI said they would love to write a rec letter saying that I am able to program just fine.

I'm thinking stuff like the Peace Corps, etc. Would doing something like that be looked at as a good thing by PhD programs? Or would it be looked down upon for being an indication of not being focused enough on stats/biostats? Or would programs pretty much ignore it and treat it as a two year gap? Asking because I'm in such a program right now and have no clue how that will impact my chances (if at all).