Nothalfgood

UMich biostat is well regarded for genetics. If one is interested in this application in particular, then this is arguably the best department in the country to be. If one is interested in anything else of the biostatistics flavor, UMich is good but arguably not the best. UMich stat is a large and fairly well-balanced department, balanced in the sense that there are plenty of people doing work in theory and in applications there. This would be a great place to be if one wanted to work in stats generally, and I think there are some people in the engineering school who do ML research with whom some stats people collaborate. However, I don't think UMich stat is known for ML or anything else like how UMich biostat is known for genetics. If I personally had the choice between these programs, then I would choose the stat department because I am interested in applications outside of the health sciences, but I would not regret ending up in the biostat department which boasts a similarly intense program and probably slightly improved outcomes for graduates considering their broadly applicable expertise.

Some people get into top programs without a math degree or the recommended minimum math coursework, but this is usually because of the research that they already do, demonstrating an interest and facility with stat methods. In my opinion, you should focus on learning what is useful, not what is required, and as it turns out all math is useful if by learning it you become a more mature proof writer and more comfortable with reading proofs that involve analysis, linear algebra, and probability all together.

I had a similar background by my senior year as you, @dirichletprior. You have already met expectations and exceeded them. Also, those who consider your application won't necessarily see your grades or course titles this coming year. You could go the route that I chose and just take a few challenging math classes in whatever sounds fun and then a few other classes that you won't be able to take in grad school. I did partial differential equations, algebraic geometry, and algebraic topology, for example, plus electives in philosophy and history to explore other interests and improve my writing skills. If instead you prefer staying more focused, then I would throw in mathematical finance as another topic that you might like to consider. An advanced course in this topic may exercise all of your statistics-relevant skills!

I'm sure there are plenty of examples of people getting into some top math programs without having a math degree, and statistics is certainly one of the most natural alternatives if you've already pretty much mastered real analysis and linear algebra, so my opinion is that it's worth a try to apply. I think there are some applied math programs that blur a lot of the lines between pure math and statistics like at UMaryland and Johns Hopkins which you may be interested in too. In some sense, you may be unable to totally "escape" applications at this point, but I think you could find stats or applied math programs where you could spend virtually all of your time working without any real data and instead on almost exclusively analysis and topology flavored problems. That is my impression from some current graduate students in statistics at schools like UMichigan and UWisconsin.

I personally would choose UIUC for the reason that I am somewhat inclined toward theory. If you don't know specifically what you want to do for research, then you will probably have more freedom to explore at a bigger department. Many biostatisticians have their PhDs in statistics, so this decision probably wouldn't close you off to opportunities after graduation. I'm sure that you will probably have to work harder on your mathematics at UIUC than Emory. If you are strongly attracted to the department culture or location of Emory, or if you are not interested in theory or a lot of math, or if you are confident that you want to do work in biostatistics, then you should not listen to my opinion at all.

Of course! The poll was just out of curiosity.

I hope you all have been having a spectabulous Spring and are excited about your options for this Fall if you have been applying to schools this season. I've been lucky to receive very good results for my PhD applications, and I do believe that I'm ready to make my decision. However, I would like to crowdsource my question just for that last drop of insight, and maybe also because I'm curious: which statistics PhD program between University of Chicago and Carnegie Mellon University would you be most inclined to choose (if those were both your best or only options)? The typical points of comparison I've approached are along these lines: UChicago has a more comprehensive theoretical program with many courses and course options, offers somewhat safer summer funding to most students, and has collaborations with nearby institutions like Toyota Tech and Argonne; CMU has more freedom built into their program without qualifying exams or as strict and intense a course load, emphasizes interdisciplinary work and applied projects more, and is located in a safer and more affordable neighborhood. I think that these may be enough to decide which department culture is more to one's general preferences, but it's not a total and unilateral comparison. I have met current students at both programs who faced the same decision, so I'm confident that there's no wrong answer. I can only truly learn about department culture by living and interacting in the respective environments. As such, I have come to a biased decision from these simple impressions alone and would like to see whether I'm approximately in agreement with the broader community of new grad students in my field.

I am reading about some summer schools in statistics or data science which are taking place (remotely) this summer, and since I find some of them interesting I thought you might, too. I'm not totally sure that all of these are open for anyone or whether they are just for in-house students or for undergrads, but my impression is that recent graduates are allowed to attend. UT-Austin has a Summer Statistics Institute May 24-27. Penn State has a Summer School in Statistics for Astronomers June 1-5. Johns Hopkins has a Graduate Summer Institute of Epidemiology and Biostatistics June 14-July 2. Princeton has a Deep Learning Theory Summer School July 27-August 4. If you have experience with one of these programs, then I would be curious to know what you think the appropriate audience is, particularly whether someone gearing up for grad school (but not yet there) should consider attending.

Undergrad Institution: Low-ranked, medium-sized public university known for engineering Majors: Mathematics, philosophy Minor: Applied statistics GPA: 4.00 Type of Student: Domestic white male GRE General Test: Q: 169 (94%) V: 166 (97%) W: 6.0 (99%) GRE Subject Test in Mathematics: M: N/A Programs Applying: Statistics and mathematics PhDs Research Experience: I attended an REU in coding theory. From this project, I got an authorship on a paper. I also attended a well known SIBS program and have done some statistics consulting for my campus writing center. Awards/Honors/Recognitions: I received a few department awards for "excellence in mathematics" and that sort of thing, and I've been a part of a few winning teams in regional math competitions. I also won a few awards for writing projects and have a pretty solid record of activities outside of math and stats. Pertinent Activities or Jobs: I have minimal experience as a TA for calculus ii, but I have a few years of experience tutoring everything from math and stats to history and writing. Letters of Recommendation: All of my recommendations came from professors in my department, none of whom are famous per se but each of whom knows me well. Math/Statistics Grades: Abstract Linear Algebra (A+) Group and Ring Theory (A+) Commutative Algebra (A) Algebraic Geometry (In progress) Advanced Calculus I (A+) Advanced Calculus II (In progress) Measure Theory (A+) Mathematical Statistics (A+) Introduction to Probability (A) Financial Mathematics (A) Design and Analysis of Experiments (A+) Regression Analysis (A+) Introduction to Applied Statistics I / II (A+ / A+) Introduction to Topology (A) Algebraic Topology (In progress) Dynamical Systems (A) Partial Differential Equations (A) Any Miscellaneous Points that Might Help: I have a pretty long list of various activities that each on their own aren't special but, when united together, form a CV so mean it makes medicine sick. (I just have a lot of extracurricular stuff. It's like I went to high school for college.) Applying to Where: (Color use here is welcome) Boston University (Math) / Rejected Michigan State University (Math) / Accepted (Declined) Northwestern University (Math) / Rejected Pennsylvania State University (Math) / Accepted (Declined) University of Illinois - Chicago (Math) / Waitlisted (Declined) University of Maryland - College Park (Math) / Pending University of Michigan - Ann Arbor (Math) / Pending University of Wisconsin - Madison (Math) / Rejected Carnegie Mellon University (Stat) / Accepted Columbia University (Stat) / Rejected Duke University (Stat) / Accepted North Carolina State University (Stat) / Accepted (Declined) Ohio State University (Stat) / Accepted (Declined) University of Chicago (Stat) / Accepted University of Michigan - Ann Arbor (Stat) / Pending University of Minnesota - Twin Cities (Stat) / Pending University of North Carolina - Chapel Hill (Stat) / Accepted (Declined) University of Wisconsin - Madison (Stat) / Accepted Reflection: I was quite anxious about my applications because I felt that my background was not brimming with research and gleaming with prestige, and I made two mistakes as soon as I finalized my list of options. Firstly, I should have been more assertive with my picks of stats programs. I didn't need to apply to every good school that I thought might accept me, and I could have reached just a little higher just for the sake it. Don't get me wrong - I'm extremely pleased with my outcomes and grateful, too. I did not expect to get accepted to Duke or CMU or UChicago and am still limited in my imagination to dream at this level. I probably could have passed on NCSU and UMinnesota, which are not as good fits for me, and instead thrown my hat in at Harvard or Stanford literally for no other reason than to see if it might've been possible. I probably wouldn't have chosen them if I did get accepted I suppose, but I admit that I do wonder. Either way, though, I realize that it would have been totally okay to take a gap year if I didn't get any acceptances for the reason that I shot too high and didn't play safely, and it would have saved me a few hundred dollars too. Secondly, I should not have gotten too excited about math programs - there's nothing wrong with math, but it's obvious to me now that I am supposed to devote my life to studying statistics. I hadn't spent a whole lot of time doing statistics, and the bells and whistles of Pure Math were always tempting me; any time I browsed YouTube or went to a math competition or attended Math Club, that spark of intellectual curiosity inside of me would jump a bit higher. I kept convincing myself that I only was considering statistics as a back-up because it's more profitable or less competitive. Somehow stats were an abhorrence, a perversion, a delinquency, and only were disguised as "a real job" in order to woo weary sailors away from that Ithaca in the ethereal Arts & Science College up above. It took some discussions with my professors and with my peers to climb down from that notion. Now I am more aware of what I want to do with my PhD, writing my statement of purpose became easier for statistics programs than for math ones. I still feel very strangely about my results, honestly. From my perspective, this is the first time in my life that I've felt thoroughly verified for something that I've cared about. I'm not especially clever nor do I have outstanding achievements. I don't attend a prestigious university. I'm like a gritty country boy with a bit of a personality and some facility with math. What helped me stand out, then? If I were to guess why my applications to statistics programs were so successful, I would say that I presented a clear and honest sense of what my goals are and why I'm applying to grad school in my statements. I think of myself as a writer rather than a statistician, and I want to train myself to be the best darn science writer I can be. I think statistics is a deeply philosophical endeavor full of challenges for writers, but it also notoriously invites opaque reasoning when efficiency is prioritized over rigor. This problem, I feel, invites people like me whose competencies conspire to address it through good expository writing, and that is the main reason why I find the subject attractive. Meanwhile, I have some technical skills and want to continue learning and studying interesting problems. I didn't pretend that I am taken by unclarifiable passions for machine learning or statistical genetics, which I don't accuse *you* of doing, but I found it hard to interrogate myself to the point that I could actually say more than that I have similar passions. The specificity and authenticity of my motivation was probably the most affecting part of my application. Toward this aspect of the journey, then, I would advise readers like me who come from more-or-less humble backgrounds to think seriously about what it is that you contribute. Prestige schools are like carnival games; it's worth the price to play. Just remember that in the academic elite people need to know who you are. You don't want to be Charlie Bucket who stumbled upon the last Golden Ticket and found his shoes on the ceiling by accident. I'm facing the fact that I will never feel like the smartest person in the room again, and I'm okay with that (although it's kind of spooky to think that there's going to be someone with a high IQ hiding under my bed). I'm excited to contribute my own experiences and ideas to whichever department I choose, and I have to know that I have that or else I won't be able to function when I get there. Not to legislate on the exception to a rule, but considering my exceptional (meaning atypical, not superior) case, I would like to conclude that there is no "correct" way for one to improve one's applicant profile. As they say, there are many paths up the mountain, but the view from the top is the same. I may not know the first thing about mountaineering, but I think it's a bit like climbing the academic ladder. There are a certain number of cliffs or steep inclines that you will find yourself facing when you choose the Road Less Traveled. You can probably find the right equipment, but you need to be a little lucky to find a good deal or else it's going to be extremely resource expensive. Actually, I don't know how to bring this analogy together. I hope my reflections have been entertaining if not insightful as well as inspiring without being pretentious.

I see. I should probably talk to more students and determine this for myself, but I appreciate hearing your thoughts.

Nope! I hope you've at least heard some good news from somewhere else by now because it's been a long wait.

Hi @kkk123117! Unfortunately I don't really have any useful advice since I'm in a similar situation you are; I'm strongly considering UChicago at this point too. Would you mind expanding on this point (quoted above)? I have gotten the impression that students in the UChicago stat department are motivated to work independently, but I'd like to know what you mean by their having more peer pressure.

For full disclosure, I'm a domestic student, and I've been accepted to a wide range of schools this season. The relative prestige of the programs seem not to correlate with the generosity of the fellowships at all based on my offers. As such, I'm personally trying not to read too much into the implications of fellowship offers on whether the departments view me as one of their top applicants or anything like that. I'd guess some of them are given to me because I'm a domestic student and others are sort of standard (like the summer teaching ones). This isn't to deflate your achievement -- I'd just suggest you factor these into your decision the way you would the stipend offers. If it means a significant difference in your quality of life, then be psyched. If it's a paltry differential, then I'd let it not be a distraction from more important criteria. I think TA requirements are like prelim requirements -- if you really don't want to teach (resp. take prelim exams), then this matters a lot, but if you don't know what to think about it, then don't worry about it. Practically everyone does it, so chances are that you'll be fine. I personally would like to teach in grad school as much as is reasonably possible, though, so don't take my word for it. What is your opinion on teaching? Do you intend to pursue a career in academia, or will it be a distraction from better things for you?

It's possible that there was a clerical error. Now I have to know: have you received any clarification back yet?

As someone who is also stuck between closely matched choices, my two cents are that you should go with your gut at this point. Everyone is telling you that you can't make a wrong pick. If you really can't peg one or the other as the best for your career, then let location and environment be the deciding factor. If that's the deciding criteria after all, it sounds to me like UFlorida is the place to go. You say you think you'd like the weather more than the others, not to mention that others cited research interests of faculty as probably a better match for you at Florida than elsewhere. I'm sure you have plenty of time to think on it, but if I were you I think it'd be as simple as that. As for my situation, I've run the same simplifying calculation as I did for yours. It's still not easy to dismiss the other acceptances I've received. I'm excited about everything, everyone, and everywhere! Why must I only choose one? I ask myself. But in the end I rationally know which program I have to go to. I'm not sure if my attitude helps with the decision, but there it is.