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Ryuk

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Ryuk last won the day on August 22 2021

Ryuk had the most liked content!

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    Statistics PhD

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  1. Anecdotally, I included two or three names in every statement of purpose I submitted and certain professors took it pretty seriously. I'm sure it doesn't matter for many programs, but it seemed to influence who interviewed me at certain departments and there were professors who assumed I wanted to be in their group, specifically. This was especially true for Berkeley. Not sure how common this is, though. I pretty much did what bayessays described when I was applying and it worked out.
  2. I am not international, but I get the feeling that stories of danger around U.S. campuses are overblown abroad. I am currently in a department located in a city that has a "dangerous" reputation and it really isn't a big deal in day-to-day life. It sounds like the location and fit of U Chicago are better and I wouldn't let scary headlines influence your decision.
  3. I agree that your profile looks good. Just to provide a balancing opinion, I think someone with a strong application like yours should apply to as many programs as possible. I also had a good profile and applied to over 20 schools. It was expensive and time consuming, but not as much as you might think. Fee waivers are easy to get and a lot of the components are the same. It also doesn't make a difference to your letter writers. I am currently attending a top institution that I definitely would not have applied to if I only chose 6 programs. I did not think I had a shot at Berkeley, Harvard, UPenn, Duke, etc., but I sent yolo applications anyway. This will likely be the biggest decision you make as a young adult, so now is not the time to cheap out. I'm not promising that you'll get into these places, but you'll never know if you don't apply.
  4. I applied to an "excessive" number of schools (>20) because I was only aiming for the top programs. It did get a bit expensive, but fee waivers were easier to get than I expected. If I had only applied to 6, I would likely not have included the program that I am attending or others that ended up on my short list. However, I understand sending fewer applications if you are mainly interested in a few programs that you are confident will admit you.
  5. It varies from school to school, but you always have to specifically request it. They won't look through your resume and do it for you. The information can usually be found by going to the stat department's application Q&A then using Ctrl+F to find "waiver". A few like Cornell list a bunch of programs that qualify but don't include the Texas State REU. There is an email at the bottom to which you can send a request for the waiver anyway. All such schools said yes when I asked for it. In short, it is very non-standardized. Some grant waivers on a university-wide basis and some on a departmental level. You'll have to search around and do some Googling to find them.
  6. I also attended the statistics REU at Texas State. A surprising number of schools gave me a fee waiver just for participating in an REU summer program. It literally saved me hundreds of dollars. I can search around and see if I stored a list of schools that did this.
  7. It seems a bit like your rankings are based on undergrad admissions. I'm not as experienced as some other users on here (who will hopefully add their opinions), but Rice probably doesn't belong in the same tier as UCB, Stanford, and UPenn. Also, UT Austin, UNC, and UW are much more selective than the other schools in your "target" category and even some of the schools in your "reach" category. Lastly, Texas A&M is a very strong program that may not actually be a safety. The US News rankings aren't perfect, but they can give you some idea of how difficult it is to get in to each of these programs (Yale and UT are outliers). As far as I'm aware, all of these programs will fund you if you are admitted, so don't worry about that until you are comparing offer letters.
  8. My impression is that the GRE can hurt you if your score is low (not applicable to you), but it isn't going to make you stand out. Things like rec letters, transcripts, interviews, and research are far more important. With a 169Q, I would stop thinking about the GRE altogether and move on to other parts of the application. If you're going to have to dedicate large amounts of time studying for the math subject test, it probably isn't worth it.
  9. I got into a few top CS PhD programs as a more theoretical applicant, but I am FAR from an expert. I had a similar research "experience" early on in my undergrad. I was given some data and a few papers, then told to find something interesting. It went nowhere. Obviously, it would be extremely impressive if you were able to produce concrete results as an undergrad with so little guidance. This would almost certainly be better than any lab work. However, it might not be realistic for you; it certainly wasn't for me. Are you applying this fall? If not, REU programs are pretty much made for your situation. The professors in an REU will ideally teach you to swim instead of throwing you in the pool like your 2 current profs. Researching is a skill that takes many years to master and is pretty much the whole point of a PhD. These summer programs are free to apply and actually pay you to attend, so there's virtually no excuse.
  10. I hope that someone with more experience chimes in to give specific predictions, but your application generally seems strong. The main weakness I see is the letters of recommendation. Two "at least positive" letters and one "did well in class" letter probably aren't enough to crack the elite schools. There isn't much time left, but it would be worth trying to form stronger relationships with these professors.
  11. I second this. I took grad classes in measure theory and probability as an undergrad, but it took a lot of preparation. I completed an "intro to proofs" course and 3 semesters of undergrad analysis before I even thought about touching anything at the graduate level. That was in addition to theoretical classes in linear algebra, numerical analysis, undergrad probability, etc. I definitely would have failed without all that prep.
  12. Undergrad Institution: Large T75 public school Major(s): Statistics, Mathematics Minor(s): Computer Science GPA: 3.96 Major GPA: 4.0 Type of Student: Domestic minority male GRE General Test: (not sent to most schools because of COVID) Q: 167 (89%) V: 165 (96%) W: 5.0 (92%) GRE Subject Test in Mathematics: NA Programs Applying: Statistics, Biostatistics Research Experience: REU at local university. Resulted in a solid bioinformatics publication in a decent journal. I was second author. Summer Program in Biostatistics at Harvard. Not as research focused as I would have liked, but still a great experience. Very applied and coding-intensive COVID project. The resulting dashboard and analysis were linked on my cv. Awards/Honors/Recognitions: Top student in honors intro to analysis (cash prize) Top student in honors real analysis (cash prize) Other small math and diversity scholarships Pertinent Activities or Jobs: Nothing outside of activities related to aforementioned research Letters of Recommendation: REU professor Math professor who was my informal advisor throughout my undergrad. COVID project professor who I also had for multiple grad classes None famous, but all knew me VERY well and promised to write excellent letters. Relevant Coursework: three undergrad real analysis classes, grad measure theory, undergrad probability, grad measure-theoretic probability, two proof-based linear algebra courses, grad Casella & Berger inference, CS courses for my minor, and many other core math and stats classes. Applying to Where: PhD only Harvard - Biostatistics / Accepted Stanford - Statistics / Rejected UC Berkeley - Statistics / Accepted Chicago - Statistics / Accepted Harvard - Statistics / Accepted CMU - Statistics / Rejected UW - Statistics / Accepted U Penn - Statistics / Accepted Duke - Statistics / Accepted Michigan - Statistics / Accepted UNC - Statistics / Accepted NCSU - Statistics / Accepted Cornell - Statistics / Accepted TAMU - Statistics / Accepted Reflection: I definitely underestimated my application. I kept telling myself that I would be happy if even one of my applications was successful. However, I received some excellent advice from my math professor: "apply to every school that you actually want to attend." As a result, I sent out 20 applications, including some CS and math programs not shown above. It took a TON of time and a good chunk of change, but I'm happy I did. If you had told me I could only send 6 applications, I definitely would have not included Berkeley, Harvard Stat, Harvard Biostat, Chicago, and UPenn. With that in mind, it was certainly a good investment. Fee waivers aren't very hard to get if money is a huge problem. Also, it doesn't seem to make much of a difference for your letter writers. They each submitted all of them in less than 30 min. Even after you take the GRE and finish your essay, the process of looking for professors of interest, tweaking your essay to fit their prompt, and just filling out the application is surprisingly time consuming. For example, some schools wanted me to submit a list of all my relevant courses with the instructor, book, and brief summary provided for each one. You'll hear it again and again, but seriously, start early. One of the main things I want to emphasize is that there is no prestige associated with my undergrad. At some places like Harvard, I was literally the only admitted student not from Ivy League, MIT, C9 League, etc. If any other admits find this post, they will immediately be able to identify me from that sentence alone. Don't count yourself out just because you don't attend a top undergrad. Before I applied, I interacted with a few grad students who put an insane amount of effort into their applications. I compared myself to them and worried that I wasn't doing enough to get into top programs. You can spend a ton of time reading books on the application process, reaching out to multiple professors at each school, etc., but I'm not sure it will make much of a difference. As long as your essay is solid, your research, transcript, and letters are far, far more important. Lastly, summer programs are a great way to get started with research. I tried a project with a prof early in my undergrad and was totally lost. After a few summer experiences, I had a publication and was able to start my own project. The applications are free, so you might as well apply over winter break and see what happens. At the end of they day, it isn't complicated but it also isn't easy. Get great grades in hard classes and do research that produces concrete results. The letters will likely follow. TL;DR: Apply to a lot of schools and don't worry about undergrad prestige. Also, attend summer programs.
  13. @MLE Fair point. I probably felt that there was a relationship because I was admitted to both and was interacting with them at the same time. I also wanted to work with Emily Fox, who seemed to bridge the gap. That weakens the argument for UW if this student is very interested in ML.
  14. UW also has a stronger CS department that is very active in ML: https://www.cs.washington.edu/research/ml. I was accepted in both the stats and CS departments at UW, and they seemed to have a close relationship with a lot of joint appointments. I am also interested in ML and would have happily gone there if I hadn't received one or two other key offers. I didn't even apply to UCLA for reasons that others have stated above.
  15. I did my undergrad in the stats department at TAMU, so feel free to ask me any questions you think I might be able to help with! I interacted with quite a few faculty, but not all of them. I definitely know the area pretty well. I literally can't say anything about Penn State, but I know that the relationship between the stats and math departments at A&M seems to be pretty strong. They are in the same building and I found it extremely easy to take classes and talk to professors from the math department. I say this because it might increase your options as far as research topics go.
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