clurp

Yes, I limited my comments to general areas and areas of application that appeal to me. I wasn't extremely specific. Have you read the thread by cyberwulf about the SOP? Maybe that will put you more at ease.

I've been struggling with this same thing. I've mostly written just a short paragraph mentioning a couple things: 1) that there is research going on in the department that aligns with my research interests 2) miscellaneous thing I've noticed about the department that appeals to me

Do grad interviews typically involve technical questions? I figured they were more about assessing fit.

I'm applying for stats PhDs and I'm having some last minute second thoughts about how I've chosen my 3 recommenders. A little background: I did math as an undergraduate (I had a > 3.7 GPA at a 'top 20' university, with math grades ranging from B to A+) I took a pretty tough schedule with a lot of upper division and graduate courses, and I participated in two summer research projects. I studied for an applied math masters in Europe for a year. During that year, I took a sequence of courses there that got me interested in statistics. The summer after the first year there, I got a job at a startup doing statistics and machine learning. I liked the job a lot and knew that I ultimately wanted to do a stat PhD, so I stayed beyond the summer and did not finish the masters. For letters of recommendation, I asked one professor that I knew quite well from coursework and summer research at my undergrad school, and I asked two PhDs (one in math, one in statistics, both from very good schools) that I work with at my current job. One has published in reputable math and stats journals and was a university instructor before his career doing quantitative research in industry. The other has published some as well, but I know less about that. The idea was that I wanted to ask the people who know me well, that I wanted to try to highlight the work I had done recently rather than 3 or more years ago, and that it's ok to have non-academic recommenders if they have PhDs and work in research. Am I wrong on that last point? I'm considering whether I ought to send a request for a letter of recommendation from another undergraduate instructor who I've previously asked for a recommendation. I got an A+ in an upper division math course of hers, although it wasn't very closely related to statistics. Should I ask her if she still has a copy of that recommendation on her computer? Is it important to have at least 2 recommendations from people currently in academia? Of course, it would be best to get another recommendation from the professor of the statistics courses which led me down the path I'm on or the professor of a graduate analysis course, but because I'm not close with those professors, I'd expect the recommendation to be generic.

I see on the application page that it says: But I was wondering if anyone has experience applying to both or can otherwise confirm that it's ok.

I think I will be applying to Columbia and Duke. Cornell's program looks good, but I don't think I'd like to live in Ithaca. I've looked at USC a bit, but had a hard time figuring out which department would be best to apply to. It seems as though they have the relevant faculty scattered through a number of departments.

That's the frustrating part. None of the individual questions in the quantitative part are hard. I guess I spent too much time reading the numbers off the data analysis charts or I spent too much time double checking that I hadn't make an arithmetic mistake or was otherwise just a little too slow. I did better on the practice tests, so I could probably improve the score. But if it's not likely to change schools' feelings about my application, then I don't want to do it. Taking the GRE isn't cheap or fun.

Sorry if this is a boring topic, but I took the GRE today. I got a 170V, 163Q. I expected a better score on the quantitative section but I timed the second section poorly and didn't have enough time at the end. My undergraduate degree is in math with a 3.76 GPA from a top 20 (USNews) school and I've taken a lot of grad level math courses. I'm applying to some of the following statistics PhD programs: Duke Carnegie Mellon Texas Washington Berkeley UCLA UNC Rice NC State Columbia Should I retake the GRE to try to raise the quantitative score? How much do programs care?

What's your motivation for wanting to learn more about set theory? That makes a difference. I just skimmed through the Halmos book online and it looks to me like it would take a lot of work for someone without much of a mathematics background to get much out of it. (Mathematicians have a habit of naming things which seems to downplay the difficulty involved in the subject. So "naive" set theory is not really so naive and you'll see graduate students walking around with books titled "algebra".)

Hi, I know it's way early to ask about "chances" for fall 2014, but I have to make a big decision soon and having a better idea about this would make that easier. I'm a US citizen. My undergrad is in math at a top 20 university (according to usnews). I had a 3.78 gpa and took a lot of math courses: a couple semesters of graduate analysis (I took the undergrad version first) two semesters of algebra, one of which only included grad students representation theory combinatorics/graph theory differential geometry a few research seminar style courses honors linear algebra honors calc courses an intro to applied and computational math (basically a matlab course) a course on bioinformatics which basically introduced some machine learning methods with python basic stats (which I took my last semester, sort of blew off and got a B+ in ) and probably some others I'm forgetting. I was pretty ambitious in my course selection, but didn't always get A's. There was a mix of A's, A-'s and some B+'s, maybe a few B's. During undergrad, I did two summer research experience things: 1) one, in a math department, resulted in a publication with many co-authors in a journal which publishes undergraduate research 2) the other was in computational neuroscience (solving systems of differential equations with matlab) I also partook in the budapest semesters program and took intro to algebra (which I've counted above), functional analysis, and topology. After graduating, I applied and got a fellowship to a masters program abroad. After the first year of that program I had a 3.72 GPA. There, I took additional courses in analysis an algebra sequence functional analysis / differential equations stats/prob a course on algorithms / theory of computing 2 courses on statistical learning / non parametric statistics and maybe some I'm forgetting. I really enjoyed the courses on statistical learning / nonparametric statistics and did well in them (kind of blew off the intro prob/stats course again though, and got a B+ :/ ), so the summer after that, I returned to the US to do an internship as a "data scientist" and continued on beyond the summer, taking a leave of absence from the master's program. At this job, I work to solve statistics/machine learning problems, mostly with R. Doing this has forced me to face a lot of problems which are central to statistics and machine learning and has probably contributed more to my understanding and passion for the subject than my previous academic work in those subjects. It's also made me a lot more knowledgable about computers. Both in order to do a better job and out of curiosity, I've been doing as much reading and MOOC participating as I can in statistics/machine learning topics. In the process, I've come to realize that I would love to do a phd in statistics, particularly something related to statistical machine learning, bayesian methods, and/or nonparametric statistics. If I went back to the master's program, I could work with the well-known professor of my statistical learning / nonparametric statistics courses on a master's thesis and possibly get a good rec from him (but by the time it would have to be written I would just be starting in earnest on the thesis and i've heard international professors are much more reserved in their praise than american professors), but i'd rather not because I like my job quite a bit and living abroad is more difficult for me now than it was when I made the decision at the end of undergrad. If I don't return to the master's program and instead continue working, I'll probably have a good recommendation from an undergraduate professor with whom I did one of the research projects (though it was quite long ago) and recommendation(s?) from phds I work with. I'm not sure how recommendations from outside academia will be viewed. Does it seem like returning and completing the program would have a big effect on my chances? Would I be likely to get into some program with researchers in my areas of interest regardless? What schools would be good targets for me?