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<record version="6" id="4335">
 <title>Simpson's rule</title>
 <name>SimpsonsRule</name>
 <created>2003-06-08 22:04:06</created>
 <modified>2006-06-15 15:20:09</modified>
 <type>Theorem</type>
 <creator id="3" name="drini"/>
 <author id="3" name="drini"/>
 <author id="2" name="akrowne"/>
 <classification>
	<category scheme="msc" code="65D32"/>
	<category scheme="msc" code="41A55"/>
	<category scheme="msc" code="26A06"/>
	<category scheme="msc" code="28-00"/>
 </classification>
 <related>
	<object name="LagrangeInterpolationFormula"/>
	<object name="NewtonAndCotesFormulas"/>
	<object name="Prismatoid"/>
 </related>
 <preamble>\usepackage{amssymb}
\usepackage{amsmath}
\usepackage{amsfonts}

%\usepackage{psfrag}
%\usepackage{graphicx}
%\usepackage{xypic}</preamble>
 <content>\emph{Simpson's rule} is a method of (approximate) numerical definite integration (or quadrature).  Simpson's rule is based on a parabolic model of the function to be integrated (in contrast to the trapezoidal model of the trapezoidal rule).  Thus, a minimum of three points and three function values are required. Here we take three equidistant points: $x_0x_2$ the interval endpoints, $x_1=(x_0+x_2)/2$ the midpoint, and let $h=|b-a|/2$ the distance between each. The definite integral is then approximated by:
\[
\int_{x_0}^{x_2} f(x) dx \approx I = \frac{h}{3} (f(x_0) + 4f(x_1) + f(x_2))
\]

We can extend this to greater precision by breaking our target domain into $n$ equal-length fragments.  The quadrature is then the weighted sum of the above formula for every pair of adjacent regions, which works out for even $n$ to
\[
 I = \frac{h}{3} (f(x_0) + 4f(x_1) + 2f(x_2) + 4f(x_3) + \cdots + 4f(x_{n-3}) + 2f(x_{n-2}) + 4f(x_{n-1}) + f(x_n)) 
\]</content>
</record>
