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kingduck

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Everything posted by kingduck

  1. I have an MS in stats, but I don't have much YOE, so my experience is based on my observations of my colleagues, and my experience may not be applicable to your situation. Several of my colleagues had business degrees or social science degrees, who ended up wanting a career change into something more technical. The more technical folks got an MS in stats, while the less technically trained folks, went for a more professional MS, like in applied analytics or masters of the sort. They were able to land a job in a more technical space, but some had down-levelled because they had no professio
  2. I am currently converting my professional resume into an academic CV (for biostat applications), which involves deleting certain skills that are only valued in the industry, and adding certain things that are valued in academia. Currently, in order, I have the sections: 1. Summary and Objective - brief TLDR of my SOP, 3 sentences 2. Education - no GPAs listed, should I? since they'll be getting my transcripts anyways... 3. Research - 3 research projects, unfortunately no publications resulted 4. Skills - I have a few coding languages in here, I used to have things like SQL, AWS, Had
  3. @HighStat I found this out on chronicle of higher education. Article is here: https://www.chronicle.com/article/more-doctoral-programs-suspend-admissions-that-could-have-lasting-effects-on-graduate-education?cid=gen_sign_in (scroll to where it shows a table of suspended programs) And an article from someone I'm in a groupchat with: https://www.outlookindia.com/website/story/opinion-what-is-the-future-of-the-american-phd/361192 (second paragraph last sentence)
  4. In light of many schools announcing suspensions in their application cycles, like Columbia's statistics program, what are your plans for applications, should more programs in other schools be suspended?
  5. Hi guys, this is about LOR strategy in the math/stat space, and I thought it might be helpful to have my profile attached as well. I wanted to know what the best strategies for getting letters of recommendations are. While I have been through the LOR process for the masters applications, I wanted to take a more nuanced approach this cycle. As mentioned previously, I have 1 professor (call him professor X) from my masters program with whom I took 2 classes with and we are currently working on 2 research topics, one on time series and one on COVID data analysis. Another professor (call him
  6. I'm in a similar boat, struggled with what I wanted for a career (hence had a low GPA), discovered math and stat as part of my degree and went on to a masters. Wanted to see if anyone else had insights on how to explain such a change in GPA and career path in the SOP, or maybe even from the recommender. I've lurked around on the forums and am also in the application cycle, so don't consider what I say as expert opinion. For a biostat program, it seems you have the requisite math courses and scored well, though you might want to have more stats. It's my understanding that UC Berkeley req
  7. Hi guys, unsure whether or not to start a new topic since this is about LOR strategy, and I thought it might be helpful to have my profile attached as well. I wanted to know what the best strategies for getting letters of recommendations are. While I have been through the LOR process for the masters applications, I wanted to take a more nuanced approach this cycle. As mentioned previously, I have 1 professor (call him professor X) from my masters program with whom I took 2 classes with and we are currently working on 2 research topics, one on time series and one on COVID data analysis. An
  8. AFAIK, Upenn does not have a terminal masters degree program in stat, and is earned on the way to a PhD, not necessarily a PhD in the stat department. That is unless you're talking about an MBA with a concentration in stat, which then has a different set of requirements different from an MS in stat.
  9. What do people think of Harvard's math 23-A for real analysis I going into a PhD program?
  10. Would AP'ing out of Calc I with a 5 score in high school be considered an A in Calc I when applying?
  11. @Casorati You know what, I just reviewed my ETS results for the GRE that I took 3 years ago, and I actually did score a 166 on the Quant. I had forgotten my score over the years lol. Now, my main concern is that my Verbal or AW score may be a bit on the lower side, or does the adcom really weigh in the V and AW scores as heavily?
  12. Thanks for the suggestions @Casorati and @bayessays. I do worry that my background, not having anything related to medical sciences, may play against me in biostat applications. I have about 1-2 years of work experience in financial data analytics, (not quant finance, just quantitative strategy and market trend analysis using statistical techniques), but I am hoping to angle my research with the professor I am working with now, to a more health related application (in light of COVID 19 there are some studies that my professor is involved in). Without the experience in medical science, is
  13. Thanks for your very helpful input! I received my masters from an R1 public school, and does have a PhD program ranked in the 40-30 range on US News. I do think that my letters will hold some weight, and the professors I am seeking recommendation from have said I am an "excellent" student, so hopefully that will translate to good LORs. They each have h-indices of 20-25, but I'm not sure if that is a fair way to evaluate their "fame" so to speak. I'm glad to hear that people with lower than A grades still make it to great programs.
  14. Hi all, I am considering applying to statistics, IEOR, and biostat PhD programs. My interests are more in the methodological side of statistics, so OR and biostat departments may be more appealing to me (leaning towards biostat), but I'm not opposed to more theoretical stats. That said, I wanted to have more insight on what should be my reach, target, and safeties for PhD applications. I would also like to point out some problems in my transcript, and see what you guys may think about it. A bit about my profile: Undergrad: Ivy League (not HYP) Major: BA in Economics (Major GPA ~
  15. Thanks for the response. I have heard of several of these OR departments, and my only concern is that they may be heavily optimization focused, which doesn't line easily with my interests. My main interest in IEOR is the application of statistics, where there is a heavier emphasis on stat methodology. I think my research interest primarily lies within the methodologies rather than the mathematical theory, which is why FE appealed to me initially, given my econ background. I've spoken to several faculty who mentioned the same as you, to broaden my scope, and to look into stat/biostat pro
  16. Hi all, I am not going to ask you guys to chance me, as I know the application cycle will be an uphill battle for me from a low GPA and non-traditional background. I majored in Economics at an Ivy League with minors in Math and Statistics. I didn't do so well in the Economics with a few C's, a few A's, and mostly B's,(major GPA ~ 3.1) while my Math (mostly A's with an occasional A-), Stat, and other STEM courses such as CompSci and Econometrics was around 3.75. My cumulative GPA including the 'general ed' courses was right below 3.40, with the lowest semester being the first semester of
  17. Hi all, I am not going to ask you guys to chance me, as I know the application cycle will be an uphill battle for me from a low GPA and non-traditional background. I majored in Economics at an Ivy League with minors in Math and Statistics. I didn't do so well in the Economics with a few C's, a few A's, and mostly B's,(major GPA ~ 3.1) while my Math (mostly A's with an occasional A-), Stat, and other STEM courses such as CompSci and Econometrics was around 3.75. My cumulative GPA including the 'general ed' courses was right below 3.40, with the lowest semester being the first semester of
  18. Hi all, I am not going to ask you guys to chance me, as I know the application cycle will be an uphill battle for me from a low GPA and non-traditional background. I majored in Economics at an Ivy League with minors in Math and Statistics. I didn't do so well in the Economics with a few C's, a few A's, and mostly B's,(major GPA ~ 3.1) while my Math (mostly A's with an occasional A-), Stat, and other STEM courses such as CompSci and Econometrics was around 3.75. My cumulative GPA including the 'general ed' courses was right below 3.40, with the lowest semester being the first semester of
  19. I've been looking at masters programs in statistics around the mid-Atlantic US region (even as far as Virginia to New Haven). I am looking for programs which will give the most help for getting into a PhD program, such as completing a thesis, having a good ratio of faculty to student in order for individual research and mentoring. Which MA/MS programs in that region are recommended for such a trajectory? I was looking at Columbia's MA program but it doesn't seem to be conducive to my goals - not saying Columbia is bad, but there may be more suitable programs in the region for those like
  20. Looking at Taheel's math courses listed, what other math courses should be taken in order to have a good math level for a PhD program? The core math undergraduate curriculum at my university is 4 courses of calculus, linear algebra, diff eq, real and complex analysis, and abstract algebra. Would these courses then be considered enough math to be considered for a PhD?
  21. Hi, This is my first post on the Grad Cafe. I'm encouraged by all of you guys because now I know that I'm not alone in this hectic time of grad applications. I am writing SOPs for MS/MA in statistics and MS data science. I eventually do want to pursue a PhD though I'm not sure which aspect of the mathematical sciences I want to be specialize in. My question is essentially: 1) What roles (software, data engineer, analyst etc)would MS data science graduates have in the industry? (whether government or commercial) 2) Would I easily have enough prior knowledge to pass qua
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