StatsG0d

To me, I don't think this is true. I think it's just that statisticians have a competitive advantage in applying Bayesian methods to social sciences (since they don't usually teach such methods in social sciences). For example, economists, which are arguably the most mathematically inclined social scientists, rely almost exclusively on frequentist regression (albeit at a very high level). So since statisticians are more familiar with Bayesian methods than economists, the former have a comparative advantage in applying Bayesian methods to social sciences.

With that profile, I'd be surprised if you didn't get into at least one of the top 3, and would not be surprised if you got into all. If you're interested in theory (presumably you are with your math background), you'd probably be happiest at Washington.

Yeah I think it's worth at least looking into some biostatistics programs. UW and UNC in particular have a lot of faculty working in ML and Bayesian analysis. Shojaie at UW is kind of a young rising star in the field and was trained by Michailidis. UW is very strong in clinical trials and Bayesian statistics plays heavily in that field. Ibrahim at UNC wrote an entire book on Bayesian Survival Analysis and hundreds of papers on Bayesian statistics. There's a good thread on here that was started a few weeks ago about statistics vs. biostatistics. I recommend you read it.

The "classical" area for this field is clinical trials.

I definitely think you're already a competitive applicant, it's just that the writing score is a little week. For most programs outside the top-10 you've got a very good shot already. I just think that improving the writing score to even a 4.0 would be good because a.) it's easily improvable and b.) it's the only true weak spot on your profile.

I definitely think you have a strong profile and I think even a marginal improvement in GRE could have a big benefit for you as it's the only true "weak" spot on your profile. Everything else looks very good to me. And as others have pointed out, the research experience makes you a unique candidate as very few people will have had that prior to graduate school. If I were to suggest something, it would be to target maybe one more of the larger programs (e.g., PSU or Purdue). I noticed others were talking about Northwestern. NU is difficult to crack even though it's ranked relatively low. Several people (including me) were rejected from NU despite getting offers from more prestigious programs. It brings up the question whether it's worth it to apply, or to invest your money elsewhere. If it were me in hindsight, I would have saved the NU money and put it towards another reach school that probably has a similar acceptance rate anyway. Also, I would check what the research strengths are and what you're interested in. For example, UNC and NCSU are both great programs and in a great part of the country, but UNC focuses mostly on probability theory and is on the smaller side and NCSU is a heavily applied department and the largest department in the country. If you know for certain you won't be interested in only applied or only theory, it might be wise to cut out some of these schools. If you have no clue what to do, your best bet is to apply to programs that are large and have strengths in both applied and theoretical areas. A&M, Purdue, and Penn State come to mind. Florida is a fantastic program if you're interested in Bayesian MCMC methods, but significantly less attractive if you're interested in almost anything else. You also might want to consider some biostatistics programs. You have loads of time, so do some research and see what sounds interesting to you. If you decide that Bayesian isn't your thing, then you can take Duke and Florida off the list and look for programs that are more suitable. After doing this, you may find you don't even need to retake the GRE. And to clarify (because I know my posts are a little confusing), I don't think your profile is weak by any means. I just think you have one weak component, but it could be offset by a strength (e.g., research experience). If you're looking to apply to schools outside the top-10 and apply to at least say 10 schools, I'm 100% confident you'll get into at least one program. But it's hard to crack that top-10.

I think Duke and CMU are far reaches. I think you'd need to improve your GRE scores drastically to have a fair chance at either of those programs. The other schools seem to be ok. I'd definitely ex off UCONN. I applied there in 2015 and they tried to admit me after April 15. I haven't heard if things had improved or not, but I think it's a risk and probably not worth the money investment. My biggest concern with your profile, however, would be the writing score. A 3.5 is not very good for a domestic applicant. And while math matters more than writing, there is at least one program (Penn State) that looks at the writing score heavily. Also, it might send a message that you cannot write analytically, which would not be a good sign for papers. This is my opinion, however, and mostly speculation. If i were you, I would consider retaking the GRE and aim for slightly improving your writing score (even a 4.0 is much better than a 3.5). When I took the GRE the second time, I improved from a 4.5 to a 5.0 without even studying for the writing portion. So study for the writing a bit, study for the math even more. Get that GRE up to a 167+ and those two programs I mentioned above are much more attainable. That being said, I had a 164 on my GRE-Q and got into some top-5 biostatistics and some top-20 statistics programs, including several of the ones you mentioned on your list.

To this question: I would say yes--they should have at least some interest in research problems that are motivated by real data sets. I would say a big difference between statistics and biostatistics is that in biostats, you're presented with a real data problem first, and then you try to work out the theory / methods to solve such a problem. In statistics, some of the research may be motivated by real data problems, but this is not necessarily so. Some are simply just about the math (e.g. probability theory). So in this regard, I would say if the OP wants ultimate research flexibility, then maybe the statistics program is better. For this I would again say I think it depends heavily on the program / with whom you are working. In most (probably >90%) cases, probably yes. On the other hand, one of my professors did his PhD at UW biostatistics and his dissertation was on martingales, which granted are useful for biostatistics, but I would not say motivated by a real life data problem. He now works in precision medicine and his students try to prove various estimators are consistent and what not. Very occasionally, this may result in proving of a new theorem. I suppose this contrasts with a statistics department. You mention Harvard, which no one will deny is a stellar program. But I think that in statistical theory, there is a *much* higher focus at UW than at Harvard.

This seems to be the thinking from many people, and while it may be true in some programs, it's not true in the others. For example, I attend a top-5 biostats program (not UW), and our coursework covers measure theory, limit theory, decision theory, etc. just like a traditional statistics program would. I don't think you can put all biostatistics programs in a vacuum and simply say "well it's biostatistics so it's less theoretical." The same goes for statistics--some even top tier programs (e.g., NCSU), will be more applied than the more theoretical biostatistics programs. We're not talking about statistics vs biostatistics here, we're talking about UW Biostatistics vs. CMU Statistics.

I don't think it's wise to choose CMU just because it's statistics and UW's is biostatistics. I definitely have seen firsthand this "arrogance" of being in a statistics department. In my opinion, it's what you research in rather than where you do your research. While the conventional wisdom is that a statistician can do a biostatistican's job but not the other way around, I would say that depends on what you do / where you do it. If you're going to say, Harvard Biostats (a great applied program), then yes--that is probably true. But Washington is one of two biostatistics programs that teach measure theory in the country (that I know of--the other being UNC). So I definitely think that this conventional wisdom is not valid, or at least it does not apply in this case since Washington does train its students in hardcore probability and statistical theory. Given your research interests (very biostat / medical themed), it seems obvious to me that you should choose Washington. If you really are torn between the two, choose whichever location would make you happier (again, I feel Washington gets the edge here). At the end of the day, people in biostats will tell you to go to biostats and people in stats will tell you to go to stats. As a final note, I definitely think biostatistics professors make (much) more than their statistics counterparts.

Knowing several students at UNC's program, I don't think funding is really an issue. As far as the tuition waiver for out of state students goes, I don't think that is true. Who would go to UNC if they had to pay tuition? If you're concerned, I'd suggest emailing a current student and asking them.

Glad it worked out for you! However, (I guess this is for the future applicants), don't think that because you studied econ you can't do stats/biostats. I also did economics in undergrad, and got into several top-20 stats and biostats programs. Best of luck in the UK!

You definitely have a pretty good shot at all those programs.

Pretty much no one has a publication record prior to grad school. I don't think that your math background is lacking. Real analysis is basically what you need to be seriously considered. I'd be more concerned with the grades you got in analysis 1 and 2.

People have gotten into A&M with far worse resumes. I wouldn't sweat it at this point.

Well, I won't lie to you and say that things look good. I'm not sure if UGA is known for its math department / grade deflation, but if neither of these things are true it will be tough to get into a high-ranking program. I think you have a decent shot at some programs ranked 20-30 solely based on the breadth of courses you've encountered, since many of those students attending those programs did not necessarily major in math. You have two semesters left so I recommend you take real analysis 2 and maybe a probability / math stats course and make sure you get an A in both. I think that will boost your profile a lot. I'm going to disagree with StateHopeful and say a regression course is not worthwhile at all. See the post that cyberwulf made about what they look in applicants. You'll learn regression your first year in grad school so there's no point in learning it beforehand. You might be able to salvage a high-ranking program if you get a very high score on the GRE and/or if you can manage to take the math GRE and perform exceptionally well >80th percentile. In fact, the Math GRE (which I am told is very, very difficult) might be your best bet to say "hey, I didn't get the best grades in math courses but I really know my stuff." Good luck.

It's nice to see that the the standard "we take a holistic approach to the application review process" is in fact true and not just something written down to keep the applicants at bay. Thanks for sharing this, @cyberwulf

I should have added dimension reduction. Thanks for adding it. That's an important discipline in stats / biostats alike.

I was browsing through and that that this is an important topic for current and prospective students alike. From my field/department (biostatistics), I can tell you that there is a large emphasis on: Genomics Precision medicine Imaging Causal inference What I would be interested in knowing / discussing is which "hot" areas in biostatistics are more theoretical. Some students prefer theory over applications or vice versa. From the above, I would argue that from more applied to more theoretical, it would go genomics, imaging, precision medicine, causal inference.

I don't really think it's necessary to retake the GRE. You have the same score as me and I got into a couple top-10 stats and almost all schools in the 11-30 range that I applied to. It will be interesting to see what happens. I think the admissions committee will forgive the relatively poor grades in the Calculus sequence if you're getting A's in analysis and abstract algebra 1 AND 2. I would say you should add maybe 2-3 more prestigious programs to that list. Try maybe Penn State, NCSU, A&M, Purdue. At A&M, it's free to apply so you have nothing to lose and everything to gain.

I don't think so. In my current program there are entering individuals ages 21-30.

You might get more responses if you use the traditional format for profile evaluations. Just look up someone else's profile evaluation on the forum and you'll see the (more or less) standard format. Good news: Your GRE is probably fine, so I don't think it's worth retaking at all. Maybe the writing score is a little low, but no one really knows how much (if at all) that factors in. Bad news: There is almost zero chance to be admitted to a (reputable) PhD program with that math background. You would AT LEAST need multivariate calculus and linear algebra. Having these two courses is the bare minimum, but may get you admitted to a program ranked 50-100. To really be competitive, you should take (and do well) in real analysis. Acing those three courses will put you in the running at legitimate programs.

Agree that it's not worthwhile to retake the GRE. Please do post your results when the time comes. I think it will help future "nontraditional" applicants. Best of luck!

I've seen people with less backgrounds get admitted to 10-20 schools, so I definitely think you have a decent shot. I would target the larger programs.

I definitely think you'd be a strong candidate for a master's degree.