Why Study Differentials?

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Discussion Overview

The discussion revolves around the concept of differentials in calculus, specifically their application in approximating changes in functions. Participants explore the relationship between derivatives and differentials, questioning their utility when discrepancies arise between differential approximations and actual changes in function values.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant explains that differentials are used to find changes based on the derivative of a function, using the example of the function y = x^2 and its derivative dy/dx = 2x.
  • Another participant notes that dy/dx represents the instantaneous rate of change, emphasizing that for nonlinear functions like y = x^2, dy/dx does not equal the average rate of change Δy/Δx.
  • Some participants express confusion about the purpose of learning differentials if they yield significantly different results from direct calculations.
  • One participant argues that differentials are effective for small changes, providing a specific example with x = 10 and δx = 1, where the differential approximation closely matches the actual function value.
  • A later reply introduces the Taylor remainder theorem, explaining that the error in differential approximations decreases as the change approaches zero, suggesting a mathematical foundation for the utility of differentials.

Areas of Agreement / Disagreement

Participants express differing views on the effectiveness of differentials, with some questioning their relevance due to discrepancies in results, while others defend their usefulness for small changes. The discussion remains unresolved regarding the overall utility of differentials in calculus.

Contextual Notes

Limitations include the dependence on the size of the changes involved and the conditions under which differentials provide accurate approximations. The discussion does not resolve the conditions under which differentials are most effective.

ShawnD
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One application of derivatives from first year calculus is something called differentials. The intent is to find the change of something based on the derivative of a function and some sort of varialbe like time or a distance or something.
Let's say you have this formula:
y = x^2
now here is the derivative:
dy/dx = 2x
now if you bring the dx over, it looks like this
dy = 2x dx

In math class, these are meant to find changes in things. Let's say you wanted to find the change in y when x changes from 5 to 10. you would just fill in the equation like this:
dy = 2(5)(5)
dy = 50

the dy is your change in y. the first 5 is your original x value. the second 5 is your change in x.

The differential said the change is 50. Now let's see what the original equation says the difference is:
final - original
= x^2 - x^2
= 10^2 - 5^2
= 100 - 25
= 75

The two different equations give VERY different answers. They're not even close. Knowing this, why do we still learn these?
 
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dy/dx is the instantaneous rate of change of y with respect to x. Since y(x) = x2 is nonlinear, you can't expect dy/dx to equal Δy/Δx
 
Exactly. If they don't work then why the hell do we learn them?
 
Because differentials work well then the quantities involved are small.

Let's stick to the [itex]f(x)=x^2[/itex] example, but with a smaller differential... how about [itex]x=10[/itex] and [itex]\delta x=1[/itex].

In this case, we have [itex]f(11)=121[/itex] and the differential approximation gives [itex]f(11) \approx f(10) + 1 * f'(10) = 120[/itex] which is pretty darn close.

The relevant theorem is:

[tex] f(x + \delta x) = f(x) + f'(x) \delta x + \varepsilon (\delta x) \delta x \ <br /> \mathrm{where} \lim_{\delta x \rightarrow 0} \varepsilon(\delta x) = 0[/tex]

In other words, the error term in the approximation of [itex]f(x+\delta x)[/itex] shrinks "quickly" as [itex]\delta x[/itex] approaches 0. In fact, if [itex]f(x)[/itex] is twice differentiable, you can prove that there exists a constant [itex]c[/itex] such that [itex]|\varepsilon (\delta x)| < c |\delta x|[/itex], so the error term is quadratic in [itex]\delta x[/itex]. (This is the Taylor remainder theorem; a differential approximation is just a first degree Taylor polynomial!)


edit: finally got the LaTeX right. :smile:
 
Last edited:
oh ok, that makes sense.
 

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