What is an easy way to calculate numerical integration uncertainty/error

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SUMMARY

The discussion focuses on calculating the uncertainty/error in numerical integration, specifically using methods such as Trapezoidal, Simpson's, and Boole's rules. The error bound for Simpson's Rule is defined as \(\frac{1}{90}(\frac{b-a}{2})^5 |f''''(z)|\), where \(z\) is a point in the interval \([a, b]\) that maximizes \(|f''''(x)|\). The source of this formula is Wikipedia, which also provides similar error bounds for other numerical integration methods. The consensus is that estimating error requires derivatives, and no simpler method exists for this purpose.

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  • Understanding of numerical integration techniques (Trapezoidal, Simpson's, Boole's)
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jephthah
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i'm measuring a waveform (pulse) that i want to integrate the area under.

i take a bunch of samples and use one of the basic numeric integration methods (Trapezoidal, Simpson's, Boole's)

what is a fairly easy method to estimate the uncertainty/error of the numeric integration compared to the "true" value?

thanks
 
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For Simpson's Rule, the error bound is:

[tex]\frac{1}{90}(\frac{b-a}{2})^5 |f''''(z)|[/tex] where z is the number between a and b that maximizes |f''''(x)| between a and b.

I got this from:

http://en.wikipedia.org/wiki/Simpson's_rule

You can find the other's on wiki as well. As far as an easier method of determining the error, I'm not aware of any. Since these methods are in some way, shape or form derived from Taylor approximations, I'm pretty sure you can't rid of taking a number of derivatives.
 

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