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Linear Algebra vs. Probability Modeling

  1. Nov 6, 2012 #1
    Hi all, I was wondering which of these two courses is more difficult? I understand the standard caveat that it depends on the institution and the professor but I'm just wondering, in terms of sheer difficulty of the concepts taught in these two courses, is there a general consensus?
  2. jcsd
  3. Nov 7, 2012 #2
    If it is proof based linear algebra then I would say that is harder. Then again I am horrible at proofs and not done much of it so some people may find that more interesting.

    Between a more applied linear algebra and probability models it is probably a toss up.
  4. Nov 7, 2012 #3
    I personally find probability modeling harder than linear algebra. But I never really had problem with proofs and stuff. But I didn't think the concepts in probability were very easy.
  5. Nov 8, 2012 #4
    No there is not a general consensus.

    Linear algebra is for many people their first introduction to proof based and abstract mathematics, and if you are not prepared for it then that can be hard, and for some people very hard. If you are able to understand proof-based and abstract mathematics fairly well, then linear algebra may be a breeze for you, but for most people it is quite challenging.

    Probability modelling (I'm assuming it is an introductory course in probability and possibly statistics) can be moderately difficult, but I have never seen anyone with the perspective that such a course is ridiculously hard (though of course it can be made so, but usually isn't). To a large extent you will learn some new concepts, compute integrals, sums, etc. Most concepts are fairly well-grounded in the real world. Sometimes it is taught together with a programmable statistics package like R, and in that case some people can find that a bit hard if they have never seen programming, but usually an introductory course is light on the programming.

    Generally I would say that the concepts in linear algebra tends to be harder, but there are also fewer of them so you spend more time on each one.

    Personally I found probability modelling harder because I had plenty of experience with proofs so Linear algebra was easy (the pace is obviously set so people who have little experience with proofs can follow).

    In the end it depends on your preferences, previous experience, and how the courses are taught (they can be taught very differently depending on the professor's philosophy and the audience).
  6. Nov 8, 2012 #5
    I should specify that it's applied linear algebra I'll be taking. I don't see why they would teach proofs in that class.

    The probability modeling class is for engineering majors.
  7. Nov 8, 2012 #6
    I remember that when I took my course of linear algebra, it seemed very abstract and complicated to grasp wat vector spaces, linear maps etc. are. But when I finally understood what this meaned, it all seemed very easy and logical. And a lot of the techniques from linear algebra are essential for physics: matrices,bases, eigenvalues...

    About probability, i also believe it's useful for physicists, not really hard but somehow quite boring
  8. Dec 24, 2012 #7
    I noticed that the prerequisite for linear algebra is just Calc 2 while the prerequisite for Probability Modeling is Calc 3 (Multivariable Calc). What concepts from Calc 3 should I expect to see?
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