Error of Simpson's, Trapezoid, etc. Rules

In summary: Here is the derivation:The error equation for the Simpson's rule, $\|E_{S}|\le \frac{M(b-a)^{5}}{180n^{4}}$, is derived from the similarity equation: $$M(b-a)^{5}=\frac{1}{2}\left(b-a\right)^{3}+\frac{1}{6}\left(b-a\right)^{2}+\frac{1}{12}\left(b-a\right)^{1}$$ The error equation for the Simpson's rule, $\|E_{S}|\le \frac{M(b-a)^{5}}
  • #1
iRaid
559
8
I learned this a while ago in my calculus 2 class and I was just thinking about it... Where do these error equations for each of the approximation rules come from? Like for example, where does the error for the Simpson's rule, $$|E_{S}|\le \frac{M(b-a)^{5}}{180n^{4}}$$ come from?

Also, why even bother learning these rules, errors, etc. when you can just compute the actual area more efficiently and effectively with a definite integral?
 
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  • #2
iRaid said:
I learned this a while ago in my calculus 2 class and I was just thinking about it... Where do these error equations for each of the approximation rules come from? Like for example, where does the error for the Simpson's rule, $$|E_{S}|\le \frac{M(b-a)^{5}}{180n^{4}}$$ come from?

Also, why even bother learning these rules, errors, etc. when you can just compute the actual area more efficiently and effectively with a definite integral?
Because there are vastly many functions that don't have nice, neat antiderivatives, so the only recourse is to do numeric integration using Simpsons' Rule, Gaussian Quadrature, etc.
 
  • #3
Mark44 said:
Because there are vastly many functions that don't have nice, neat antiderivatives, so the only recourse is to do numeric integration using Simpsons' Rule, Gaussian Quadrature, etc.

I understand that, but where do they get the equations from?
 
  • #4
Most books on numerical integration show how the formulas are derived. A few that I have on hand are
Applied Numerical Analysis, Second Ed., Curtis E Gerald
Computer Approximations, John F. Hart et al.
Elementary Numerical Analysis: An Algorithmic Approach, S. D. Conte and Carl de Boor
 
  • #5
Mark44 said:
Most books on numerical integration show how the formulas are derived. A few that I have on hand are
Applied Numerical Analysis, Second Ed., Curtis E Gerald
Computer Approximations, John F. Hart et al.
Elementary Numerical Analysis: An Algorithmic Approach, S. D. Conte and Carl de Boor

Do you mind posting the derivation? I only have one calculus book (Stewart) and it doesn't have it.
 
  • #6
Try a search online. Someone almost certainly has it posted already.
 
  • #7
Ok I found a derivation online, it seems very complicated though lol. I see why my book would leave that out.
 

1. What is the Error of Simpson's Rule?

Simpson's Rule is a numerical integration method used to approximate the area under a curve. The error of Simpson's Rule is the difference between the exact value of the integral and the approximation obtained using Simpson's Rule.

2. How is the Error of Trapezoid Rule calculated?

The Error of Trapezoid Rule is calculated using the formula: E = -(b-a)^3 / 12n^2 * f''(c), where a and b are the limits of integration, n is the number of subintervals, and f''(c) is the second derivative of the function at some point c in the interval [a,b].

3. What is the significance of the Error of Simpson's and Trapezoid Rules?

The Error of Simpson's and Trapezoid Rules gives an indication of the accuracy of the numerical approximation of the integral. A smaller error indicates a more accurate approximation.

4. How can the Error of Simpson's and Trapezoid Rules be minimized?

The Error of Simpson's and Trapezoid Rules can be minimized by increasing the number of subintervals (n) used in the approximation. As n increases, the error decreases and the approximation becomes more accurate.

5. Is it possible to completely eliminate the error in Simpson's and Trapezoid Rules?

No, it is not possible to completely eliminate the error in Simpson's and Trapezoid Rules. However, by increasing the number of subintervals, the error can be made as small as desired and the approximation can be made arbitrarily close to the exact value of the integral.

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