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timmmythetooth

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Everything posted by timmmythetooth

  1. I went last year and had a great time. There is basically zero pressure placed on you, so don't worry about reading up on professors or dressing sufficiently formally. At this point, you are essentially interviewing them, but anticipate laid-back, informal conversations nonetheless.
  2. cyberwulf- I'm not sure I saw a single statistics department that had measure theory as a prerequisite when I was applying. Maybe one or two that said it could be helpful. Regarding the original question, a Harvard PhD stats grad I talked to said that the department there teaches very little measure theory.
  3. You may be underestimating the strength of Berkeley and Washington if you don't consider them top schools; check out the USNEWS rankings. I think they are decently representative of statisticians' views, though rankings only go so far. However, your profile looks pretty strong to me. Statistics programs often don't have many prerequisite Statistics courses, and your strong math background is more important. The only omission that may be important is the lack of a formal Mathematical Statistics course, but I wouldn't worry too much about that, especially since you're studying it on your own anyway. Most programs do want you to have some knowledge of programming, though (the more the better), and I don't see any mention of that. The hiatus won't necessarily hurt you, I think. PhD programs are very much like a tough job with low pay, and the increased maturity one can gain from working in industry for a bit can be a plus. However, it is very important that you frame your motivations properly in the statement of purpose. You don't want to come off as simply bored with your career, and make sure you highlight a desire to develop new methods and do research, rather than practice data analysis on its own. Also, statements about how statistics is increasingly relevant in a world with increasingly ubiquitous data are about as ubiquitous as the data are. I would guess that admissions committees read something similar in many of the SOP's they read, so I'd recommend avoiding saying such things directly (even though it's a totally valid statement). And finally, that was all geared towards PhD admissions, but if you were instead interested in MA programs I think you would be quite competitive everywhere.
  4. If you are exclusively doing statistical analyses of relatively small datasets, without the need to really interface with larger systems/applications, R alone is probably fine. For anything more, I'd recommend also learning Python since it is both extremely versatile and easy to use. C is a very important language in the grand scheme of things, but it's not for the faint of heart. Unless you really need to write lightning-fast code doing things in Python is fine. Finally, some knowledge of databases could definitely come in handy. And unless you have reason to do otherwise you should start with some form of database that uses SQL (mySQL, PostgreSQL, etc). Not too hard to learn either.
  5. You may know this, but CMU will not have a great deal to offer for bio-related stuff, unless you're interested in neuroscience (Rob Kass and others from CMU and Pitt are working on very cool things in in the Center for the Neural Basis of Cognition). Very nice program in general, though. I believe you can apply to both Stat and Stat/Machine Learning, but Stat/Machine Learning is very difficult to get into, and I would expect successful applicants to have a good deal of CS background. Like the above poster I find it strange that you would reject UW for quality-of-life reasons, but I'm biased, as I'll be going there next fall. Regarding NCSU and Duke for Stat, my impression is that CMU and Duke are about equally difficult to get into, with the small size of Duke perhaps making it a bit tougher there, while NCSU is easiest (doesn't mean easy, of course!) of the three. CMU is by far the most attractive of the three to me, but I don't know about bio connections at Duke/NCSU.
  6. Undergraduate Institution: Small, private Top 50 U.S university Major: Math BS, Computer Science BS GPA: 4.00 GRE: Verbal 170, Quant 166, AW 4.5 Graduate Institution: N/A Important Classes: Foundations of Analysis, Real Analysis, Linear Algebra, Numerical Computing, Probability Theory, Mathematical Statistics, Statistical Analysis, Lots of CS Research Experience: Worked with professors at my institution for a senior thesis and a URP Publications: 1 perhaps upcoming Grants: None Teaching experience: Worked as a math mentor for Calc 1 and as a tutor for elementary school students LORs: 2 from professors of Industrial Engineering with whom I've done research, one from Math professor of course where I was top student. One LOR from full professor of IE was stellar. He in fact offered me a job as a consultant with his company after our research experience. Second IE professor probably gave a pretty solid rec, as I did very well in his Mathematical Statistics course and had also begun research with him on a problem in operations research. Third rec was very good for a Did Well in Class rec, but as we all know these only go so far. Applied (all Stat PhD): Washington, CMU, Harvard, Berkeley, Wharton, Duke, Michigan, Minnesota, UCLA Accepted: CMU, Washington, UCLA, Michigan, Minnesota (not officially, told them I was no longer interested when gauged for interest at "top" of wait list) Rejected: Harvard, Berkeley, Wharton, Duke Declined: UCLA, Michigan, Minnesota Attending: Either CMU or Washington (Extension until May 1)
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