Molar conductivity - Revision history

en>Inwind: clean up, disamb using AWB

2014-12-11T10:15:40Z

clean up, disamb using AWB

← Older revision		Revision as of 12:15, 11 December 2014
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	~~{{Other uses\|Truncation error (numerical integration)}}~~		Hi there. Let me begin by introducing the author, her title is Sophia Boon but she never truly liked that name. What me and my family adore is bungee leaping but I've been taking on new things recently. I am an invoicing officer and I'll be promoted soon. Ohio is where her house is.<br><br>Look into my blog post accurate psychic predictions [[http://srncomm.com/blog/2014/08/25/relieve-that-stress-find-a-new-hobby/ srncomm.com]]
	~~In [[numerical analysis]] and [[scientific computing]], '''truncation error''' is the error made by truncating an infinite sum and approximating it by a finite sum~~. ~~For instance, if we approximate the [[sine]] function~~ by the ~~first two non-zero term of its Taylor series~~, ~~as in <math>\sin(x) \approx x - \tfrac16 x^3</math> for small <math>x</math>, the resulting error~~ is ~~a truncation error~~. It is ~~present even with infinite-precision arithmetic, because it is caused by truncation of the infinite [[Taylor series]] to form the algorithm~~.

	~~Often, truncation error also includes [[discretization error]], which is the error that arises from taking a finite number of steps in a computation to approximate~~ an ~~infinite process~~. ~~For example, in [[numerical methods for ordinary differential equations]], the continuously varying function that is the solution of the differential equation~~ is ~~approximated by a process that progresses step by step, and the error that this entails~~ is ~~a discretization or truncation error~~. ~~See~~ [[~~Truncation error (numerical integration)]] for more on this~~.

	~~Occasionally, [[round~~-~~off error]] (the consequence of using finite precision [[Floating point \| floating point numbers]] on computers) is also called truncation error, especially if the number is rounded by [[truncation]].~~

	~~== References ==~~
	* {{Citation \| last1=Atkinson \| first1=Kendall A. \| title=An Introduction to Numerical Analysis \| publisher=[[John Wiley & Sons]] \| location=New York \| edition=2nd \| isbn=978-0-~~471~~-~~50023~~-~~0 \| year=1989 \| page=20 }}~~
	* {{Citation \| last1=Stoer \| first1=Josef \| last2=Bulirsch \| first2=Roland \| title=Introduction to Numerical Analysis \| publisher=[[Springer-~~Verlag]] \| location=Berlin, New York \| edition=3rd \| isbn=978-0-387-95452-3 \| year=2002 \| page=1 }}~~.

	~~[[Category:Numerical analysis~~]]

en>Yobot: Reference before punctuation detected and fixed using AWB (9585)

2013-11-07T22:02:10Z

Reference before punctuation detected and fixed using AWB (9585)

← Older revision		Revision as of 00:02, 8 November 2013
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	I'~~m Luther but I~~ by ~~no means really liked that name~~. ~~I am~~ a ~~cashier and I'll be promoted soon~~. ~~I've usually cherished living~~ in ~~Idaho~~. ~~What she enjoys doing~~ is ~~playing croquet~~ and ~~she~~ is ~~trying to make it~~ a ~~occupation~~.~~<br><br>Also visit my website: auto warranty~~, [~~http://Www~~.~~Shownetbook~~.~~com/enone/xe/?document_srl~~=~~3029968 click the up coming webpage~~],		{{Other uses\|Truncation error (numerical integration)}}
			In [[numerical analysis]] and [[scientific computing]], '''truncation error''' is the error made by truncating an infinite sum and approximating it by a finite sum. For instance, if we approximate the [[sine]] function by the first two non-zero term of its Taylor series, as in <math>\sin(x) \approx x - \tfrac16 x^3</math> for small <math>x</math>, the resulting error is a truncation error. It is present even with infinite-precision arithmetic, because it is caused by truncation of the infinite [[Taylor series]] to form the algorithm.

			Often, truncation error also includes [[discretization error]], which is the error that arises from taking a finite number of steps in a computation to approximate an infinite process. For example, in [[numerical methods for ordinary differential equations]], the continuously varying function that is the solution of the differential equation is approximated by a process that progresses step by step, and the error that this entails is a discretization or truncation error. See [[Truncation error (numerical integration)]] for more on this.

			Occasionally, [[round-off error]] (the consequence of using finite precision [[Floating point \| floating point numbers]] on computers) is also called truncation error, especially if the number is rounded by [[truncation]].

			== References ==
			* {{Citation \| last1=Atkinson \| first1=Kendall A. \| title=An Introduction to Numerical Analysis \| publisher=[[John Wiley & Sons]] \| location=New York \| edition=2nd \| isbn=978-0-471-50023-0 \| year=1989 \| page=20 }}
			* {{Citation \| last1=Stoer \| first1=Josef \| last2=Bulirsch \| first2=Roland \| title=Introduction to Numerical Analysis \| publisher=[[Springer-Verlag]] \| location=Berlin, New York \| edition=3rd \| isbn=978-0-387-95452-3 \| year=2002 \| page=1 }}.

			[[Category:Numerical analysis]]

203.192.229.180 at 17:03, 4 June 2012

2012-06-04T17:03:15Z

New page

I'm Luther but I by no means really liked that name. I am a cashier and I'll be promoted soon. I've usually cherished living in Idaho. What she enjoys doing is playing croquet and she is trying to make it a occupation.<br><br>Also visit my website: auto warranty, [http://Www.Shownetbook.com/enone/xe/?document_srl=3029968 click the up coming webpage],