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Moment


Thenthraw momentmu_n^' (i.e., moment about zero) of a distributionP(x) is defined by

 mu_n^'=<x^n>,
(1)

where

 <f(x)>={sumf(x)P(x)   discrete distribution; intf(x)P(x)dx   continuous distribution.
(2)

mu_1^', themean, is usually simply denotedmu=mu_1. If the moment is instead taken about a pointa,

 mu_n(a)=<(x-a)^n>=sum(x-a)^nP(x).
(3)

Astatistical distribution isnot uniquely specified by its moments, although it is by itscharacteristic function.

The moments are most commonly taken about themean. These so-calledcentral moments are denotedmu_n and are defined by

mu_n=<(x-mu)^n>
(4)
=int(x-mu)^nP(x)dx,
(5)

withmu_1=0. The second moment about themean is equal to thevariance

 mu_2=sigma^2,
(6)

wheresigma=sqrt(mu_2) is called thestandard deviation.

The relatedcharacteristic function isdefined by

phi^((n))(0)=[(d^nphi)/(dt^n)]_(t=0)
(7)
=i^nmu_n(0).
(8)

The moments may be simply computed using themoment-generatingfunction,

 mu_n^'=M^((n))(0).
(9)

See also

Absolute Moment,Characteristic Function,Charlier's Check,Cumulant-Generating Function,Factorial Moment,Kurtosis,Mean,Moment-Generating Function,Moment Problem,Moment Sequence,Skewness,Standard Deviation,Standardized Moment,VarianceExplore this topic in the MathWorld classroom

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References

Papoulis, A.Probability, Random Variables, and Stochastic Processes, 2nd ed. New York: McGraw-Hill, pp. 145-149, 1984.Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. "Moments of a Distribution: Mean, Variance, Skewness, and So Forth." §14.1 inNumerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, pp. 604-609, 1992.

Referenced on Wolfram|Alpha

Moment

Cite this as:

Weisstein, Eric W. "Moment." FromMathWorld--AWolfram Resource.https://mathworld.wolfram.com/Moment.html

Subject classifications

Created, developed and nurtured by Eric Weisstein at Wolfram Research

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