orchidnora

Hi there. First of all, is there a reason why you want to jump straight into a Ph.D.? Given your background, it might be more efficient to complete a Master's in CS/Stats/related fields. I have heard that some of these programs like having applicants from industry and other academic backgrounds. Then if you still want the Ph.D., you will be in a much better situation to apply for top programs. If you do prefer to get another Bachelor's, I can offer some advice on that. I don't think that being out of school for three years will significantly affect your chances in a negative way. But I think you will have to gain some research experience, like all applicants (traditional background or not), before being admitted to top Ph.D. programs. Moreover, it would be good to ensure that you like research, before committing to a five year Ph.D. program. It's not necessarily a problem that your school has limited research opportunities, since you can find research opportunities elsewhere (you can apply for summer NSF-REUs, government internships through NIH, U.S. Census Bureau, DOE labs, etc., although it might be difficult to get these positions until after more than 2 semesters of coursework...). But keep in mind that pursuing a Ph.D. typically means a willingness to move anywhere for the best research and career opportunities, so staying in NYC might restrict your options. Also if your school has limited ongoing research in general (meaning that there are few researching professors and graduate students) then you may consider attending a better school. Unfortunately, the rankings of an undergraduate institution do matter to some extent in graduate applications (Bs at MIT probably count more than As at an unknown school).

Typically, for top stats Ph.D. programs, it’s best to take as many theoretical math courses as possible. Generically, functional analysis might look best if you can get a good grade. However, if you want something directly applicable to applied statistical research, I would recommend taking nonparametric stats. An at least basic understanding of these methods is necessary imo for many data analysis projects. Of course, if you don’t take it now, you’ll probably end up seeing it in grad school anyway. On the other hand, if you really enjoyed Stochastic Process I and might wanted to study it in grad school, then take Stochastic Process II. Really, it’s up to you: how you want to spend your semester and what you intend to do in grad school. When applying you’ll have the SOP to emphasize any strengths in coursework, so think about what you want your coursework to represent about you.

Thank you for the info! This is very reassuring. It seems my recommendations will also only be a little late (less than one day late). At this point, it's out of my control, since I already sent a reminder and don't want to harass my recommender. I will probably call admissions on Monday just for sanity.

It's so stressful! And for some deadlines, I think you're right. But others are different, for example, Harvard is due 5 P.M. Eastern today.

Unfortunately, my recommenders have missed the December 1st (November 30th 11:59 P.M.) deadlines. Anybody else nervously awaiting their letters? Hopefully this won't affect anyone's chances of acceptance....

Thanks, ya'all! In that case, I will upload the papers as supplementary documents, keeping in mind they probably will not be fully read. Hopefully my recommenders have discussed my contributions to the work.

Hi, everyone! I have some papers already available online (and I provided the links to them in my CV submitted for graduate applications). Is it a good idea to also upload the papers as supplementary documents in grad school applications? I'm concerned that application reviewers may not notice the provided links, while the papers are hard to miss when submitted as supplemental documents. I'd love to hear anybody's thoughts! Thanks.

There are many top scores on the quant portion of the GRE. 160 is about 75th percentile, 165 is about 88th percentile, and even a perfect score of 170 is still only 97th percentile.

I assumed that publications meant papers, books, etc. Typically, nobody would consider a poster or presentation slides to be publications, especially since (presumably) there was no peer review. In each of my my applications, there was a separate area to list presentations, so you could list them in an area like that. Also list them on your CV/resume. You could also attach PDFs of your posters as supplemental documents

Can anybody confirm if schools actually care if you submit a resume or a CV? Stanford specifically states to submit a resume, but I also would prefer to submit my CV, which is much more detailed.

Hi, everyone. This is a somewhat specific question, but I'm sure there are other people on here required on the UCB application to submit a course list. The Statistics Department at UCB requires a list of all upper-level coursework completed. Does anybody have experience with this and know how long the description for each course should be? Can I simply copy and paste the course description from my university's website, or is it supposed to be a separate description of topics that I write myself? These are the instructions: "Please include the department, course number and title, instructor, grade, school, texts used and subject matter covered for all upper division and graduate level statistics and math courses you have taken. You should also include courses outside statistics and math departments that have a significant quantitative component. This list should be uploaded as a PDF document via the online application."

I appreciate everyone's advice here! Qualification for fellowships is definitely an important consideration. All things considered, I think I will write the diversity statement but be very cautious with what I say and how I say it.

@Stat PhD Now Postdoc: Thank you for your advice. In that case, I will move forward writing the diversity statement. I will be sure to discuss my experiences in an honest, neutral manner and avoid any entitled or grandiose statements. I am glad to know that my experiences will probably be viewed favorably by admissions committees. @Moods: I was mostly worried about being "judged" by researchers on the admissions committees, but you bring up an excellent point that those researchers would be unpleasant to work with anyway. The conversation you linked is very helpful. Thank you for your insightful comments - you're right that the statement will offer another glimpse of me to the admissions committee. Good luck in your application as well! @Gauss2017: That is true, I am an American white female. Unfortunately, I was not very active in any clubs at my school, so I did not participate in any women in math or women in STEM groups. I can't say I have experienced any blatant issues from classmates or professors as a woman in math/stats. Of course, I am one of a few females in my theoretical math classes, and there have been subtle comments or incidents with causes I can speculate.

Hi everyone! Like many people here, I am applying to the University of Washington (for a Ph.D. in Statistics). A personal statement is strongly recommended, but unlike typical personal statements, this one emphasizes diversity. On the one hand, I have encountered certain obstacles that have impacted my life (raised by a single mother and had financial troubles growing up, neither of my parents hold Bachelor's degrees, received essentially no financial support while in college forcing me to take out loans and work while in school, etc.). But none of the obstacles are directly relevant to what I plan to research in statistics (e.g., I'm not planning to research ways to reduce inequity in society ). Despite any disadvantages, I have excelled in college and have a strong application. Also I have quite a bit of teaching experience in statistics, where I have reached students from diverse academic backgrounds; additionally, I volunteered for a semester to tutor and mentor a middle schooler deemed "at-risk". Although I hope to mentor student researchers in the future, my career goals are primarily research-based. In light of this information, should I write the diversity statement? If I opt not to write the diversity statement, will it negatively affect my admissions (UW claims it will not, but I am skeptical)? If I do write the diversity statement as someone who already has a strong application, could it somehow harm my chances of admission? What if somebody in the Statistics department is against "diversity culture" and refuses to work with me? For reference, I have copied and pasted all the information on the statement provided by UW: "***A Personal Statement is optional but strongly recommended. We welcome applicants from culturally diverse backgrounds. Consistent with our goal of enhancing the intellectual excellence of the department and University of Washington community, we actively welcome students from encourage all applicants to submit a personal statement (maximum 1 page) that details experiences related to your socioeconomically disadvantaged, disability-related, and/or culturally varied background, and/or experiences working with such groups. The statement should address the ways your experiences have affected the development of your intellectual interests, career plans, future goals, and how you may have overcome various obstacles or aided others in surmounting such challenges. While admission decisions are made mainly on the basis of academic performance, applications will be reviewed with consideration of the applicant's background and experiences. We also use the information in such statements to report aggregate data to funding agencies and to apply for funding diverse backgrounds and students who have worked with diverse groups. We present opportunities for eligible students. The personal statement is not required, and you may include a simple sentence such as "I have not yet had these kinds of diverse experiences." Such a statement does not negatively affect your chances for admission."

Thank you for your help. I will add these to the list as well.

Somebody probably knows better than I do whether it is worthwhile to retake the GRE. But if you do retake it, keep in mind that you have the option on test day to see your raw scores immediately afterward and send either a) the most recent scores (if they have improved) or b) send all your scores. Alternatively, you can wait until after you leave the test center and select to send any score you want (so the earlier scores if you did better there), although then you will have to spend the $27 per score report. So even if your scores do drop, the only cost is wasted time and money. Also I have personally found there is a lot of variation in GRE scores seemingly by random chance (or unknown factors). My quant scores have ranged from 158 to 170 (including only my official GRE scores and scores from ETS practice tests I took under test day conditions) and did not correlate perfectly with the amount studied. This high variability is part of the reason why I believe the test is flawed and that scores should include some measure of error/variation. Anyway, my point is that even if you DON'T study at all, there is a reasonable chance your scores will increase by chance imo.

Thank you! The reason for the gap is that I am trying to avoid very cold places (I know it sounds petty, but this is the most important "quality of life" factor for me). But I will certainly add NCSU to my list and see if there are any others in between Duke and UCLA.

Hi everyone, could you evaluate my profile and recommend any other schools to apply? Thanks in advance! Undergrad Institution: Large top 10 public university (according to US News) Major(s): Math and Stats (double) Minor(s): GPA: 3.99 (All As except one B+ in a gen ed freshman year) Type of Student: White female domestic student GRE General Test: 165 Verbal, 165 Quant, writing score and percentiles unavailable so far (but I got a 5.0 writing score last time, so I'm expecting something similar) Math Subject Tests: I took it, but I'm not expecting great scores. I'm sending them to Stanford but probably won't send them anywhere else. Programs Applying: Ph.D. in Statistics Research Experience: a) NSF REU over the summer in applied statistics and machine learning b) A year long applied statistics project with a professor at my university c) A computing research internship over the summer at a national lab (project was in statistics but with a computational flavor) Awards/Honors/Recognitions: Dean's List every semester Expecting to graduate with Summa Cum Laude Honors in Statistics because of my high GPA and an undergraduate thesis (I will use one of the papers from my research projects for it) Won best oral presentation at a regional math conference for undergraduate and graduate students Pertinent Activities or Jobs: TA for a statistics course for my 5th semester now Letters of Recommendation: From projects a) and b) I'm expecting two very strong letters of recommendation from two statisticians, respectively. From research project c), I'm expecting a decent letter from an applied mathematician who supervised the project. Relevant Coursework Non-Theoretical Math: Calc 1-3 (univariate and multivariate), ordinary differential equations, biological modeling Theoretical Math: Linear Algebra, Abstract Algebra, Real Analysis (2 semesters), Modern Analysis (currently taking and expecting an A; this is the first analysis course Ph.D. students in math take at my school) Statistics: Probability, Statistics Theory, Regression, Experimental Design, Categorical Data, Multivariate Data, Nonparametric Data, Time Series Programming: Java Programming (now I mostly program in R) Posters and Presentations a) Student poster at JMM, poster at a supercomputing symposium at my university, 15 min oral presentation as JSM, 15 min oral presentation at the regional math conference previously mentioned c) Student poster presented at lab, numerous oral presentations for certain groups at the lab Publications a) First author on a non-refereed paper, first author on a paper that we are currently working on (it will not be published in time, but I will attach the draft as a supporting document in my applications) b) First author on a paper submitted for publication (it will not be published in time, but I will include the paper as a supporting document) Research Interests I'm mostly interested in high-dimensional statistics and manifold learning, motivated by real-world applications and requiring intensive computational methods/resources. Applying to Where: UC Berkeley, UC Davis, UC Los Angeles, University of Washington, Stanford, Duke, Harvard, maybe UNC Chapel Hill Thanks again! ?