mathfriend

NCSU sent out an email to admitted students indicating that online instruction is a possibility for the Fall, and that funding will be impacted. They also suggested that they might allow students to defer a year, in which case you wouldn't have to worry about a more competitive pool next cycle. I know that we'll manage somehow, but I know that in my Master's, it's been so important to have a good group of colleagues I can talk through problems with. It will clearly be more difficult to form those strong connections if next Fall is online. I'm hoping there will at least be an in-person orientation so we can get a chance to know our cohort, but who knows.

Thank you all for the insight. I have many friends who've (successfully) negotiated higher stipends (in Law, for example) - truly it does happen! However, if you say that this is not common practice in Stats, I believe it. I actually had one Stats department ask me to send them a competing offer if I had one before they finalized my package, but this is consistent with the idea that any additional fellowships/scholarships would have already been considered before the offer reached me.

I know that in other fields it's common for accepted students to present competing offers to their school of choice in an attempt to increase their stipend. Is this done at all in Statistics departments? I have an offer from UCLA, and am very interested in the research there. However, the stipend would pretty much only cover rent. I have offers from better-ranked programs (similar dollar amount, but much lower cost of living), and some higher dollar-value offers as well. Is there any chance of negotiating a higher stipend?

Just got a phone interview at UCLA (with the professor I expressed interest in and would genuinely be very excited about working with). I'm not sure what to expect, but I'll be thinking about my answers to the questions in the google doc. Thank you @ENE1 for sharing!

Does anyone have any knowledge about Statistics at UC San Diego? I see that they offer a PhD in Math with Specialization in Stats, but there appear to be only 6 faculty doing Stats research, so I'm a little apprehensive that my opportunities might be limited there. My research interests are many: high-dimensional stats, machine learning, causal inference, spatio-temporal data and climate applications.

I just got an acceptance from NCSU (Stats PhD). I am pleased, but also now very anxious about hearing from others now that I know they're starting to make offers - I thought I had a little more time before I had to start worrying! Applied to: UCLA, UCI, UC Davis, UC Berkeley, NCSU, Duke, Harvard, Caltech (all Stats PhD's, except Caltech CMS).

Thank you for the sanity check.

Having read the pinned post on research statements, I am still feeling uneasy about indicating potential advisers in my statement of purpose. The conventional wisdom in just about any other field seems to be that you should reach out to and engage in a dialogue with potential advisers before writing your statement of purpose . Is that really not the case in Statistics? I've tried emailing a few professors whose research called out to me, but I haven't had a response. I'm wondering if I need to write more compelling emails, or if this just is not an approach that works in Stats. So far, only a few of the programs I'm applying to ask you to specifically indicate who you'd like to work with - should I do it anyway for the rest? Is it risky if I say that I'd be interested in working with someone and it turns out that person isn't taking grad students currently? It feels like a difficult balancing act: I want to write with enough specificity to demonstrate maturity in the subject, yet I don't want to pigeonhole myself. Thank you!

Thank you for your input. Boston U and UCSC had been on previous incarnations of my list and I will give them a closer look. After sleeping on it, I realized that my real concerns about my application are that I have research experience but no publications, and that all of my most recent Math courses were from a state school (with a good Math department) rather than my more prestigious undergrad. And to clarify my geographic concerns: I have a strong preference for California, but have friends and have spend time in Boston and NC and would consider those as well. Thanks again!

Hello, I’m a current MS student in Math (expected graduation Spring 2020) applying to PhD programs in Statistics for Fall 2020 and am looking for feedback on my tentative school list - apologies if this is posted in the incorrect place or manner! Undergraduate Institution: Top 10 US public university Graduate Institution: Local state school Majors: Economics GPA: Undergrad 3.96, Grad 4.00 Type of student: White female Relevant Courses: Undergraduate: · Introduction to Statistics (A+), Econometrics (A), Applied Econometrics (A) · Calculus I -III , Linear Algebra and Differential Equations (A) · Proof writing (A) · Intro Mathematical Probability , Mathematical Statistics I, II (A) · Advanced Calculus I, II (Real Analysis I, II) (A) · Abstract Algebra, Number Theory, Advanced Linear Algebra (A) · Numerical Analysis (A) Graduate: · Topology (A) · Measure Theory (A) · Multivariate Statistics (A) · Computational Statistics (IP) · Calculus on Manifolds (IP) GRE General: Q170 (96), V170 (99), AW5.5 (98) GRE Subject: I really don’t want to take it! Research Experience: Year long project in probability, presented at a conference, summer project in machine learning presented at a big conference and papers submitted (but I probably won’t hear back in time), current thesis in regression methods for complex data structures (being as vague as possible here because it’s pretty niche). Work Experience: Two years at a think tank, supervisor on a Math REU, instructor of undergrad mathematics (labs and lectures). Honors and Awards: a bunch of university based awards. Letters: All from Math/Stats professors, all but one of whom I’ve done research with. I expect them to be very strong. Interests: Are varied – causal inference, algebraic statistics, machine learning, anything with good theoretical meat. Concerns: I don’t have any formal training in Computer Science, but I’ve done extensive work in Python, Matlab, R (mostly R). I’m having a hard time narrowing my schools down based on research interest, since there’s so much I’ve enjoyed – all I know is that I don’t want Biostats. Am at any kind of disadvantage having an MS already? I know there are many undergrads who have about as much graduate math as I do, but my undergrad was in another field. Schools: I am obviously biased towards CA. All programs are Statistics PhD’s unless otherwise indicated. · Reach: Berkeley, Harvard · Target: NCSU, Duke, UCLA, UC Davis · Safe: UCSB, UCI, UCSD (Dept of Math and Statistics), JHU, Colorado State Questions about schools: According to US News, UCI is ranked 50th, but looking around here I’m seeing it referred to as a strong program. What am I missing? I wish I had a more realistic “reach”, but I’m very geographically biased. Suggestions? Thank you!