cyberwulf
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Posts posted by cyberwulf
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It doesn't hurt to reach out and let them know you remain very interested. If it comes down to the end and they're filling the last couple of spots, a student who expressed strong interest and seems highly motivated to come is more likely to get the offer than someone they haven't heard from since they applied.
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I wouldn't bother. Admissions committee members aren't going to read your paper, so the difference between something that's in-progress and something that's submitted/on arXiv is pretty minimal.
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I'd be very surprised if any program uses an application system that has year-to-year "memory" the way you describe. At most, some application reviewers might vaguely remember your name from last year.
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That's a very good publication record for a Masters student, but publications aren't the only metric used for PhD admissions. You'll need to provide more information to get a decent read on your chances.
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On 9/28/2022 at 1:29 PM, conflitz said:
Thank you so much! Do you think my application would be competitive for top programs?
Undoubtedly.
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One bad grade isn't going to sink you, but it's a little unfortunate that your outlier is one of the small number of proof-based math courses that undergrads take. If you have good grades in classes at a similar level of rigor (e.g., real analysis), then that will help a lot.
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For better or worse, sports statistics isn't widely recognized as a "serious" research sub-discipline. The faculty at highly-ranked places who work on it mostly have it as a side interest rather than a primary focus. While this perception is slowly changing, it creates challenges for folks like you who are interested in pursuing serious statistical work on the topic. I guess my advice to you would be to try to get into the best Ph.D. program you can that has at least one person who appears to have an active interest in sports analytics. So, if everything aligns, you have an opportunity to work in this area, but if your interests broaden or shift (which is common), then you're still at a good place.
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I don't think your GRE score does much to change your profile. Also, there's no harm in mentioning COVID as a mitigating factor in your Masters performance as part of your SOP.
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I would add more schools in the 5-15 range (NC State? Carnegie Mellon? Michigan?) as I suspect that is about the range where you will be competitive. With your profile, I don't think it would be a waste of time applying to a top 3 program.
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Your math background and grades are well short of what is needed for admission to any well-regarded stats PhD program (e.g., US News Top 50). If you can afford it, your best chance to improve your standing is to get into a decent Masters program and rock it there with great grades and meaningful research experience.
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Your profile is pretty unusual, as it's uncommon to see someone who graduated from a solid undergrad with a near-perfect GPA proceed to get mediocre grades in a relatively unknown Masters program. Those B's in math stat (and to a lesser extent the B+ in Real Analysis) is going to raise some serious concerns about your ability to "hack the math" at many of the higher-end places you're applying to. You might be able to overcome these concerns with really strong letters or if there is some compelling explanation for your lower grades in more challenging math courses. Given all this, I think your list is reasonable; places like Texas, Minnesota, UCLA, Emory, and Wisconsin are probably reaches but the other programs on your list are more achievable.
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90 hours? I'm not sure I believe that for one week, let alone a whole summer. In fields like stats and biostats, where virtually all of your work time involves intense thinking or doing (unlike lab-oriented fields where a decent chunk of "work" time is waiting for experiments to finish), it's just not possible for most humans to put in more than 50 or so productive hours per week. In grad school (at a top program), I was probably putting in about 40 hours/week spread across 7 days; some weeks less, others a bit more but rarely more than 50 and certainly never exceeding 60. I don't think I was way outside the norm.
If you have to put in anything near 90 hours per week on a regular basis to be successful in a program, then I would argue that you're in the wrong program (or, at the very least, should be looking for a different advisor).
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There will be a lot international applicants with a profile similar to yours, i.e., solid grades at a respected school and a little bit of research experience. You may be at a slight disadvantage compared to applicants who came to the US for their Masters degree. A lot will depend on where you studied; for example, if you went to one of the SKY universities (Seoul, Korea, Yonsei) then your chances will be better than if, say, you went to Zhejiang, where there is more grade inflation and a 3.7 is somewhat less impressive. I would say that the places you mentioned as main targets (UConn, Pitt, Penn State, OSU, etc.) are reasonable, and if you apply to several you should feel pretty confident about getting an admissions offer. I would suggest supplementing your list with some more "reach" schools (Wisconsin, UNC, Michigan, etc.) which may not even be reaches depending on the details of your academic profile.
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18 hours ago, Kaz_KV said:
This is super helpful - thanks! Just curious, should I largely focus on research fit/interests in the SOP? I know that's the norm with social science PhDs but I was unclear about if 'stem' fields had different expectations (due to some advice I received from a friend in an engineering phd).
You may not have specific research interests yet, which is fine. I would recommend focusing on what drew you to biostatistics and what types of problems you might be interested in working on. As I've posted before, the SOP just isn't that important unless your profile is way outside the norm (and yours isn't).
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Not only do you have a shot at those “reach” schools, it’s entirely possible you could get into all of them with solid grades in your remaining quant courses. There’s an enormous gap in competitiveness between MS and PhD admissions.
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@bayessays is absolutely correct; you're so far beyond the needed prep for a Masters program that I wouldn't even bother addressing your lower grades in super-advanced coursework.
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I have to say your list of programs is rather unusual. UW and NYU aren't in the same universe biostat-wise (UW is a top three program, NYU's program barely registers though they've got some good faculty). You'll likely get into any MS program you want, so I think you should focus on your PhD list, and take a long look at programs in the 5-15 ranking range (Michigan, UNC, Minnesota, Berkeley, Penn, Emory, Columbia, etc.) where I suspect you'll be competitive.
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I predict you're going to get in everywhere for a Masters. You would likely be competitive for PhD admission at most of the places on your list.
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I think your list of schools is pretty reasonable. The top 15 programs are likely out of reach based on your GPA (both undergrad and grad), and it's unlikely that the letters from your supervisors are going to be strong enough to overcome that. However, you have applied work experience, so might be an appealing candidate for more applied programs.
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@bayessays Yes, most biostat programs admit 50% or more domestic for funding (training grant) reasons, but the applicant pool is usually >70% international. So the probability of being admitted is lower for international students.
Also, this profile isn’t particularly impressive for a domestic biostat applicant in 2021; solid performance at a decent undergrad followed by average performance at a decent MS program is borderline for admission to a top 10 program.
(By the way, @LeoStat, please don’t take this the wrong way. Your results could be quite good with strong letters, and I hope my sense of your chances is overly pessimistic!)
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I'm going to be a little bit of a downer here and say that I wouldn't bet on getting into a top 10 biostat program. The applicant pool has gotten insanely deep, and even places outside the top 5 can now afford to accept only the top handful of international students who apply. At our (top 10) program last year, I would estimate that we saw 30-50 international applicants with profiles at least strong as yours; we admitted fewer than 10.
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Do you have guaranteed funding at McGill? It can be a challenge to secure that in Canada.
Overall, FSU has stronger faculty than McGill, but Erica Moodie at McGill is a star and an obvious choice to work with if you're interested in causal inference.
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On 5/24/2021 at 9:18 PM, trynagetby said:
Harvard, Berkley, UW Stats all have at least 3 very top/rising star type people doing causal inference research. An important distinction you have to make is whether you want to do "classical" causal inference (propensity scores, average treatment effects, instrumental variables, potential outcomes framework) or "modern" causal inference (dags,judea pearl causal discovery, reinforcement learning, adaptive designs etc...). Both are pretty hot right now but the flavor of research is extremely different.
This is a great answer. Another way of thinking about the distinction is that there is theoretical (= "classical") causal inference, which is about defining and exploring the properties of new estimands and identification approaches, and there is methodological/applied (= "modern") causal inference, which uses the potential outcomes framework and techniques from causal inference to answer specific scientific questions. I tend to think of the former when I think of the term "causal inference"; the latter includes several areas that don't carry the causal name: precision medicine, dynamic treatment regimes, treatment effect heterogeneity, etc.
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5 hours ago, StatsG0d said:
If you have the prerequisites, epi and econometrics are good disciplines for causal inference research as well.
I wouldn't recommend that someone go to an Epidemiology Ph.D. program with the intention of doing methodological research in causal inference. Outside of Harvard (and to a lesser extent UNC), I can't think of any Epi programs with multiple faculty doing causal methods work.
In the current tenure-track job market for stats PhD's, are we seeing more post-docs or more fresh PhD grads land assistant professor roles?
in Mathematics and Statistics
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In biostatistics, I'd say that 75% or more of new hires at top 20 places have a postdoc under their belt. But it's certainly possible to get hired straight out of a PhD.