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How to make a meaningful contribution in computational research?

  1. May 15, 2012 #1
    Hey,

    I will soon learn to code and would like to get a feel of how it's used in scientific research. I was thinking of using Python as it's used in physics a lot (apparently) and there are a lot of resources for it, even an OCW course.

    I know a prof who might be able to let me contribute a little to his work. I haven't asked him anything yet but he's really cool and I'm sure he'll at least consider it. He works on fluid dynamics, biostatistics, geostatistics, financial math and numerical linear algebra.

    My understanding is that making a meaningful contribution would be much easier in something computational as opposed to something like pure math. I don't expect to do anything extraordinary but I would just like to know what I should be learning in order to make a convincing case to that prof? I don't want to waste (too much of) his time. Apparently R is used a lot in geostats, so perhaps I should learn that instead?

    Thank you.
     
  2. jcsd
  3. May 15, 2012 #2
    You might want to check out this book Numerical Recipes (website: http://www.nr.com/) for some ideas.
     
  4. May 15, 2012 #3

    chiro

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    Science Advisor

    Hey Mepris.

    R is something that is a good idea to learn especially for quantitative analysis and modelling. If the data you are using is manageable (i.e. not too large or complex), then this is a very good idea.

    In terms of getting results quickly, I don't think it's easy to beat something like R considering the number of packages for R is extensive and what the packages can do matches that in a good way.

    There are packages for all kinds of techniques including matrix techniques, statistical and probabilistic techniques, as well as methods to create fancy graphs with customization using one or two lines of code.

    You can do work in R that relates to all the areas you have mentioned, but I imagine you will have specific kinds of analyses for particular methods and particular sub-specialties within these areas themselves.

    You can download R freely and all the packages and also the documentation as well.
     
  5. May 15, 2012 #4
    Thank you. I will keep this in mind for future use.

    Hey Chiro,

    Thank you for all the information.

    How would you recommend I go about learning R? I understand that you have been programming for a long time now, so perhaps you don't know of any n00b-friendly tutorials/books, but in case you know of some, throw 'em my way!
     
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