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cyberwulf last won the day on December 7 2017

cyberwulf had the most liked content!

About cyberwulf

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    Latte Macchiato

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    Not Applicable
  • Program
    Biostatistics (faculty)

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  1. As others have said, you need to take more math. You got a 'B' in one of the two most advanced math classes you've taken (LA), which is going to raise some red flags regarding whether or not you'll be able to navigate more rigorous coursework. Also, unfortunately, you won't get a lot of credit for your organizational and leadership work. Not because it's not important, but because it's difficult to gauge the extent of any individual applicant's involvement in such extracurricular activities.
  2. Wow, you have a very distinctive profile. The key question that MS admissions committees are looking to answer is: "Can this person pass the required courses (and if applicable, the Masters exam)?" Unfortunately, your performance in pre-req courses provides some fairly strong evidence saying "no". However, other aspects of your record (GRE scores, letters) are more consistent with a "yes" answer. So programs are going to have to figure out how to balance those when considering your application. Interestingly, you might be one of the only cases I've seen where you have a better chance of admission to a PhD program than a Masters program. That's because "upside" (read: research potential) is a bigger factor in PhD than Masters admissions. Your case rests almost entirely on an "upside" argument, i.e., that it is worth overlooking a weak academic record because you bring other, harder to quantify skills to the table. In addition, there are generally more funding streams available to support URM students in doctoral programs than Masters programs. Before you apply, I would urge you to carefully consider and articulate why you think you're now a good bet to succeed in coursework similar to (and likely more challenging than) stuff you've struggled with in the past. While it may be uncomfortable to revisit your past performance, making that case strongly is going to be vital to your success.
  3. cyberwulf

    Post-Doc and Assistant Faculty Position

    Since around the time of the financial crisis (2008-2010). In those years, there were very few jobs to go around and so a lot of graduating students ended up in postdocs. Then, when those folks went out on the market a couple of years later, they looked "better" (i.e., had more publications) than graduating Ph.D. students, and the pattern was established. Yep, volume has exploded and I don't quite know what to make of it either. The cynic in me says that advisors are wielding a much "heavier hand" in helping their students (and even postdocs) prepare papers. Regardless, it's a vicious cycle; people with long CV's get jobs, which incentivizes everyone to try to bulk up their publication list as much as possible. This aligns with everything I've seen. The applicant pool has gotten much, much deeper in a relatively short time. I don't know if the top end is any better, but the sheer volume of very good applicants is staggering. It's hard to expand Ph.D. programs quickly. You have to identify sources of funding for students, and hire enough faculty to advise them. I think you are seeing some amount of program expansion, but it clearly hasn't kept pace with demand for spots. Of course, the "data science" craze won't last forever; just ask computer scientists about the late '90s and early '00s.
  4. cyberwulf

    Fall 2019 Statistics Applicant Thread

    It's not time to freak out yet. It's common for programs to "batch" applicants so that the admissions committee isn't faced with an enormous pile to review at the same time.
  5. A lot depends on how highly regarded your "small liberal arts college" is. Williams, Amherst, and Pomona (for example) seem like they would qualify as "small", and having a 3.95 from one of those schools would likely put you in a strong position to be admitted to some very good (think top 10) programs. If by "small" you mean "not well known/regarded". then your results might be more uneven.
  6. cyberwulf

    Prestige vs. Fit

    Here are a few good reasons to choose a "prestigious" program: 1) It's very difficult for students (and even faculty) to gauge the quality of a faculty member "at a glance". Having a large number of faculty working in one area doesn't necessarily mean a department has strength in that area. Faculty at higher-ranked departments are, on average, "better" than faculty at lower-ranked places, so you don't have to rely as much on your own judgment. 2) Targeting a particular faculty member (or small group of faculty) when deciding on a program is risky. Faculty may leave/retire/change research areas/go into senior administration/etc. This is a particular concern at a lower-ranked place; if a faculty member is truly excellent, they are more likely to be "poached" by a higher-ranked place, asked to serve in higher admin at their current institution, etc. 3) Following from the first two points, higher-ranked programs generally offer better "fall-back" options if your original research plan doesn't pan out. At top places where most faculty are field leaders, switching advisers and research areas won't typically have a big impact on your future prospects. 4) The student cohort matters. Not only is it motivating and inspiring to be around other top-tier students, but an underappreciated benefit of going to a top program is the academic network that you build from being there. Knowing people in academia means you are more likely to be invited to give talks at other institutions and at conferences, more likely to be asked to be a reviewer or associate editor for a journal, etc. And, a few reasons not to: 1) Sometimes it's better to be a big fish in a small pond. If you're one of many excellent students at a good place, it's easier to get lost in the shuffle. 2) Top places tend to be pretty big, and you may prefer a smaller environment. 3) Faculty members at prestigious programs are under a lot of pressure to maintain a high level of productivity. This can create an intense environment that may be sub-optimal for student learning/advising. For example, advisers may feel that they can't be as patient with you if they need to get stuff finished and published quickly to be competitive in their field.
  7. Since neither White nor Asian are UR categories (so you're likely not eligible for any UR-targeted scholarships/fellowships), your answer to that question should have zero impact on your application. If it did, whoever was handling admissions would be in blatant violation of the Civil Rights Act.
  8. cyberwulf

    Multivariate Calc on transcript

    Yeah, if you've got 'Analysis II' on your transcript then everyone will assume you've already done multivariable calc.
  9. Whoa, that sure blew up in a hurry. My perspective is this: An admissions committee is not in a position to assess the degree to which your illness affected your grades, or whether it is a persistent problem that will continue to affect your performance. Further, as @Gauss2017 notes, it is clearly illegal to use this kind of disabling condition as the basis for rejecting you. I think the best thing to do here is the simplest: Just say that you were ill for a period, and this negatively affected your grades. Most, if not all, admissions committees will take you at your word and adjust their assessment as they see fit.
  10. cyberwulf

    Undergrad research in area other than stats

    Wrong, wrong, wrong! Very few undergrads have done "meaningful" (i.e., publishable in good journals) research in statistics before they apply. Hence, committees look for evidence of research potential, which can certainly be inferred from contributions to research projects in some other field. Plus, your research advisor will hopefully say nice things about your intellect, work ethic, etc. that are relevant to any field.
  11. Supplementary papers most likely won't get read. There's simply not enough time, and it's also difficult to gauge how much the student contributed to the work (that's where letters come in).
  12. The reality is that it's hard for prospective students to gauge exactly what a department's strengths are. Probably the best indicator is to look at what recently graduated students are working on, and where they got jobs. If graduates in a particular research area got jobs at good places, that's likely an indicator that the institution they graduated from has some strength in that area. Of course, with such small numbers involved, this isn't an exact science.
  13. It's fine to mention that this is not an ongoing issue, but you don't need to say much more than that.

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