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Why learn integration techniques?

  1. May 26, 2008 #1
    if most integrals aren't integrable to and can be evaluated numerically to any degree of accuracy why learn these esoteric techniques at all?
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  3. May 26, 2008 #2

    matt grime

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    Why bother learning any maths if a computer can solve it all numerically....?
  4. May 26, 2008 #3


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    Math isn't just about finding solutions to equations - when it comes to proving theorems computers are rather useless in many cases. And even when computers can help us prove theorems - it's only when there're to many special cases for a person to examine, the four color theorem for example.
  5. May 26, 2008 #4

    Gib Z

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    Why learn how to differentiate when taking a very close finite difference will do?
  6. May 26, 2008 #5

    D H

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    Be careful here. For example, it is often claimed that [tex]e^{-x^2}[/tex] is not integrable. That of course is not true. The integral of this function is very well-known:
    [tex]\int_0^x e^{-t^2}dt = \frac{\surd \pi} 2 \text{erf}(x)[/tex]

    When mathematicians say something isn't integrable what they really mean that the solution cannot be expressed in terms of some limited set of functions, typically the elementary functions. If an integral comes up often enough mathematicians (or physicists, or whoever) will define a function based on this integral. The error function is one such special function.

    That one has to resort to numerical techniques to solve a numerical problem is not limited to the special functions. What are the exact values of [itex]\surd 2[/itex] and [itex]\sin 1[/itex]? We have to use numerical techniques to evaluate [itex]\surd 2[/itex] and [itex]\sin 1[/itex], even though both the square root and sine functions are elementary functions.
  7. May 26, 2008 #6
    No, integrability means excatly what it means, that functions' riemann sum converges, and the limit of this is called riemann integral.
    a function which isn't integrable in a specific domain, means that its riemann sum doesnt converge.

    at least this is one way of defining integrability.
  8. May 26, 2008 #7

    D H

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    Loop, while that is one way of defining integrability, it obviously is not the sense meant by the original poster. What the OP really meant was (my changes to the OP are in italics):

    "if most antiderivatives cannot be expressed in terms of elementary functions but can be evaluated numerically to any degree of accuracy why learn these esoteric symbolic integration techniques at all?"
    Last edited: May 26, 2008
  9. May 26, 2008 #8
    yes that was a mistake on my part.

    yes i don't see anything odd about using a numerical method for a numerical problem such as evaluating a definite integral.

    this begs the question: what are antiderivatives used for other than elegantly evaluating definite integrals.

    actually nm that question cause i'm sure there exists a use somewhere, maybe proving certain things or some such thing.

    but calculus classes are for engineers, why do they need to learn these techniques? i'm not an engineering student i don't know but i would guess their integrals are simple??? even if they are why waste their time when everyone these days has access to some way of evaluating them numerically.

    that's not a very good rebuke because i don't need to resort to finite differences unless i'm taking discrete data which most people don't do.

    before i get a lot of people rebuking me note that i think the ideas behind the indefinite/definite integral and derivative are very important, it's the rigamarole i don't see the necessity of.
    Last edited: May 26, 2008
  10. May 27, 2008 #9

    Gib Z

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    I don't get what you mean by having "to resort to" them, my point was that taking close finite differences can give us the numerical value for the derivative at that point to any degree of accuracy, just as numerical integration techniques do for integrals. I thought this parallel might have made the answer a tiny bit easier to see, but it obviously doesnt, my bad :(

    My point was, exact answers are always nice =] And when we can't get an exact answer, call it something new.
  11. May 27, 2008 #10
    And I think that's a good question, to wit I have a bad answer (*cough* speculation *cough*).

    I think that many students haven't fully mastered algebra when they begin learning calculus. They can do algebra, but they can't think with algebra. In the process of doing all those limits, derivatives and integrals they obviously gain an intuition for calculus, but they also only then truly become adept at thinking with algebra. And that is crucial for doing well in physical science and engineering.

    I say this because my students at the beginning of the year had no problem doing algebra, but they really struggled with interpreting and understanding algebraic equations even when they understood the physical concepts. By the end of the year, that really wasn't a problem. Now certainly you can attribute it to both physics and calculus, but I have a feeling that calculus played a stronger role in that learning process.
  12. May 27, 2008 #11


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    Integration is not always about finding the numerical value of an integral. Just pick up any book on pure mathematics. You'll most likely find integrals on every page, but not one of them will be evaluated to give a numerical answer. In fact, you can even just look at any book on physics or engineering. Most results will involve symbolic integration as intermediate steps in the derivations.
  13. May 27, 2008 #12
    and what is exact to be exact? is [itex]\sqrt{2}[/itex] exact? sure but who cares because you can't do anything with that symbol except algebraic manipulation. i would say derivatives are useful because we can always take a derivative of a continuous function and it's quicker than finite differences, that was my point.
    i'm going to get lynched for this one but that again is a completely pointless thing im my humble opinon. anyway then symbolic integration is a tool for research engineers and physicists not practicing engineers. meaning of course i had in mind all the phenomenology that goes on in physics when i asked this question hence i restricted it to engineering. i guesss i should've been more specific about what kind.
  14. May 27, 2008 #13


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    If you don't understand how integration works, why should you have any reason to expect that the number your computer is giving you will be accurate? Black boxes that give you magical answers can be dangerous things. If you don't understand how the program does things, you run the risk of getting an erroneous answer out of it. This might not be a large problem if you're a research scientist just trying to solve an integral to use in a calculation you're doing for a paper, but if you're an engineer and a computer gives you the wrong answer you could end up with a collapsing bridge. In order to understand how programs do integration, you need to know how integration works - convergence of the integral, how many bins you need to accurately represent the area under the curve, etc.

    Furthermore, there could be issues of efficiency. Some integrals can be transformed into other integrals which could be easier to solve numerically. If you're writing your own integration problem you need to know how to work with integrals if you're going to turn the integral you have into something nicer to evaluate numerically.

    Lastly, what if the integral you need to do is a simple one, or one with problem points that might cause a computer grief due to singular points that are easily dealt with symbolically? Why waste time getting a program to numerically solve [itex]\int_a^b dx~\ln x[/itex] when you could easily find the integral to be [itex]\left[x \ln x - x\right]_a^b[/itex]? The computer would have a much easier time evaluating [b ln b - b] - [a ln a - a] than summing up several bins.
    Last edited: May 27, 2008
  15. May 27, 2008 #14


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    You clearly have no idea what engineering is. Post this in the engineering forum and see what they say.
  16. May 27, 2008 #15
    how about instead of me double posting you give me an example since that is the point of this thread.

    Mute i've already addressed your points.

    Look I'm not a polemicist, let everyone keep that in mind. For what it's worth I'm a pure math student so I'm not some lazy dunce trying to argue their way out of learning abstract concepts.
    Last edited: May 27, 2008
  17. May 27, 2008 #16

    The truth is that we teach integration techniques so that we can employ professors into mathematical research en masse.

    If you want a better answer (in terms of morality, but only equally true in the world), calculation is part of the mathematical tradition and without it pure mathematics would collapse. The problem is that now that you don't care about calculations, you are one step closer to not caring about theorems. As you can see by looking at history, the criteria for what is a theorem and what is a mere example always shift in a more jaded direction over time --- towards the view that more and more is trivial --- but if we follow this trend to its logical conclusion we see that math will die of the same snob-strangulation that kills technique in other fields.
  18. May 27, 2008 #17
    Say you have to evaluate this integral 100,000 times for various values of "a" (this is a completely realistic scenario if you are simulating something)

    \int_0^a \frac{1}{x^{0.999}}dx

    which do you think is faster: Waiting for some numerical algorithm to converge, or to do it by hand?

    Or what about a function that oscillates like crazy? It takes a while for that one to converge too.
  19. May 27, 2008 #18
    I think a much more interesting question would be "why bother learning integration techniques when Mathematica can usually symbolically evaluate integrals for you?"
  20. May 27, 2008 #19


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    In my opinion, teaching the techniques allowed me to appreciate how technology shortened the many many integrals that I have had to do by hand.(And most of those, were long and nasty looking!)
  21. May 27, 2008 #20
    Actually in your case doing it by hand is still slower because you still have to evaluate the antiderivative 100,000 times. Simply use an algorithm that's quadrature based on rational functions (as opposed to polynomials) in C code and a home pc will beat you to the punchline. Even if you allow yourself the use of a scientific calculator when you evaluate that function 100,000 times!
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