Accuracy of f(x) when x is Accurate to 6%”

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Discussion Overview

The discussion revolves around determining the accuracy of the function f(x) = x^{1/4} when the input x is accurate to within 6%. Participants explore various methods to calculate the percent error in f(x) based on the given accuracy of x.

Discussion Character

  • Mathematical reasoning
  • Exploratory
  • Technical explanation

Main Points Raised

  • One participant expresses uncertainty about how to derive the percent error in f(x) from the given information about x.
  • Another participant suggests differentiating dy/dx and using the percent error for dx to find dy, although they are unsure of the method's correctness.
  • A later reply provides a formula for delta f based on the derivative and the percent error in x, concluding that the percent error in f is a quarter of the percent error in x.
  • Another participant agrees with the previous calculation but suggests a different approach, indicating that using a calculator could yield a more straightforward answer without calculus.
  • This participant calculates the minimum and maximum values of f(x) based on the 6% variation in x, revealing an asymmetrical relative error in f(x) compared to the symmetrical relative error in x.
  • They also note the importance of establishing that f(x) is monotone increasing for the calculations to hold, warning that this may not apply in cases where f(x) has local extrema.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best method to determine the accuracy of f(x). Multiple approaches are discussed, and there is uncertainty about the necessity of calculus versus direct calculation.

Contextual Notes

Some participants highlight the need to consider the monotonicity of f(x) in their calculations, indicating that the results may vary in different contexts where f(x) has local extrema.

huan.conchito
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Suppose [tex]f(x) =x^{1/4}[/tex] . If x is accurate to within 6%, within what percent is f(x) accurate ?

i know that %percent error = delta F/ f(x) = f'(x)*deltaX / f(x)
what i don't know is how to get delta f out this this information
 
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anyone know ?
 
I think I ran into this in calc, but not quite sure, I believe you can differentiate dy/dx, then you could plug in the %error for dx, then solve for dy. That probably isn't it but its my best guess at the moment so late at night for me right now :-p
 
[tex]\Delta f = \frac{df}{dx}|_{x_0}\Delta x[/tex]
[tex]\Delta f = \frac{1}{4}x_0^{-3/4}\Delta x=\frac{1}{4}\frac{x_0^{1/4}\Delta x_p}{100}[/tex]

where [tex]\Delta x_p[/tex] is your percent error in x and x0 is the value of x at which you're finding the error. To get the percent error in f, you just evaluate:

[tex]\Delta f_p=100\frac{\Delta f}{f(x_0)}=100\frac{\Delta f}{x_0^{1/4}}=\frac{1}{4}\Delta x_p[/tex]

In other words, it's just a quarter of the percent error in x. If you're just looking for the raw error in f, it depends on the value you're evaluating at and it's given by the second equation above.
 
Ah that is indeed it, if you used the method I said before, you would actually need to plug in .06x, not just .06, then solve for dy and divide by the function leaving you with 1.5% I believe.
 
Honestly, there is no need to use calculus for this, unless a calculator is forbidden. You can get an exact answer much more easily directly with a calculator.

[tex]f(x) = x^{\frac{1}{4}}[/tex]

We're given that the maximum error in x is 6 %, meaning that x varies from a min of 0.94x to a max of 1.06x

Hence,

[tex]min(f(x)) = (0.94x)^{\frac{1}{4}}[/tex] which approximately equals to [tex]0.9847(x^{\frac{1}{4}}) = 0.9847f(x)[/tex], meaning a percentage error of - 1.53 %

and

[tex]max(f(x)) = (1.06x)^{\frac{1}{4}}[/tex] which approx. [tex]1.01467f(x)[/tex], meaning a percentage error of + 1.47 %

So you can see the relative error in f(x) is assymetrical for a symmetrical relative error in x, and goes from a maximum of 1.53 % on the negative side to a max of 1.47 % on the positive side.

To be rigorous, you actually need to establish that f(x) is monotone increasing for the domain in question (true in this case). But it wouldn't work, for instance, in cases where there is a local maximum or minimum to f(x) around the values in consideration. And example of this would be in computing the relative error in [tex]f(x) = (x-1)^2[/tex] for a 5 % error in x where x is known to be close to 1.
 

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