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statprospect

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    Statistics

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  1. You might also want to bone up on some basic statistical programming. You could try reading through The Art of R Programming by Norman Matloff. He has a copy of the pdf freely available on his website (http://heather.cs.ucdavis.edu/~matloff/132/NSPpart.pdf).
  2. Apply early. Some schools consider an early round of applicants so you are competing with a smaller pool. Also, cast a wide net. The application process is a bit of a crapshoot. I got into some very good programs and was rejected by programs that would generally be considered much less competitive.
  3. Thank you and congratulations to you as well mathgirl! Are you also deciding between a stats and biostat program? This is a tough call for me since at the biostat program, there is a lot of opportunity to take classes in that university's stats department - they actually take the same core and quals. There are also many students in biostat there who have statistics professors as advisors. I think that the difference is that the statistics department I was admitted to could be said to be generally more theoretical in terms of the research interests of most professors. I would presume that this has some impact on the type of students I would be studying with, which I am not sure is something I should consider. There may be something to be said for having more theory oriented peers going through classes with you. It has been a bit difficult to pin down what the general feeling is on this issue among faculty at my current institution. Most professors seem to agree with you, but a handful, including the director of graduate studies here, seemed to feel that it would be much more difficult for someone with a biostats degree to get an offer at a statistics department unless he had a really outstanding cv. I feel like I am trying to decide whether to eat a very delicious apple or a very delicious orange. This is in some ways an unreasonable question to ask other people, since the most reasonable response would be for others to just ask me which I like better. To butcher the metaphor further (sorry), they could both go into a very delicious fruit salad (i.e. help me get to where I want to be), so the question ultimately boils down to which fruit salad customers like best and is most marketable.
  4. An RA offer is a research assistantship appointment.
  5. Hi everyone. I have two very good offers for PhD programs, one from a top 2 biostat department, the other from a top 10 statistics department (most people would probably say in the 5-8 range). I am trying to weigh the pros and cons of choosing one over the other and was hoping that you could shed some light on the problem. The offers are materially the same in total (though biostat is an RA while stat is a TA), although even if they were different I would not be so concerned about it. I am really wondering more about whether or not I would be limited in terms of career choices, especially in academia, if I chose the biostat program. I prefer the location of the biostat program, but probably wouldn't suffer in either place. In terms of coursework, the biostat program is probably a bit more targeted towards applications, but it is flexible enough that I could (and would) be able to take the standard theory courses that I would have in a pure stat program. In terms of my research interests, I love statistics. If I had to choose an area of application, which is something that I think would be important for me to do even if I ended up doing research in theory and methods, it would probably be biostatistics. With that said, I am a very intellectually curious person, so I am sure that I would probably enjoy other applications as well. Thoughts? Thanks for the help!
  6. Hi Everyone, I am planning on beginning a PhD program in Statistics next fall, and am trying to figure out which courses to take next semester in preparation. I am trying to decide between the following two classes and would really appreciate any insights any of you might have. Graph Theory: A Combinatorial View - An introductory course in graph theory with emphasis on its combinatorial aspects. Basic definitions, and some fundamental topics in graph theory and its applications. Topics include trees and forests graph coloring, connectivity, matching theory and others. Complex Variables - Fundamental properties of the complex numbers, differentiability, Cauchy-Riemann equations. Cauchy integral theorem. Taylor and Laurent series, poles, and essential singularities. Residue theorem and conformal mapping. I am also taking Fourier Analysis, a doctoral class on statistical computing (optimization, sampling, etc.), and a class on analysis and optimization. Thanks!
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