The 1937 massacre is a central moment in Hispaniola's history, and is vividly recounted in Michele Wucker's " Why the Cocks Fight : Dominicans, Haitians, and the Struggle for Hispaniola, " a complex exploration of the cultural divide between Haiti and the Dominican Republic.
42.
And finally, one Democrat said, even if the White House was not behind the attacks, days of stories questioning Kerry's account of this central moment in his biography had the effect of reinforcing a main line of attacks on Kerry-- that he was not trustworthy.
43.
The first raw moment is the mean, which, being odd, does not exist . ( See also the discussion above about this . ) This in turn means that all of the central moments and standardized moments are undefined, since they are all based on the mean.
44.
The first cumulant is the expected value; the second and third cumulants are respectively the second and third central moments ( the second central moment is the variance ); but the higher cumulants are neither moments nor central moments, but rather more complicated polynomial functions of the moments.
45.
The first cumulant is the expected value; the second and third cumulants are respectively the second and third central moments ( the second central moment is the variance ); but the higher cumulants are neither moments nor central moments, but rather more complicated polynomial functions of the moments.
46.
The first cumulant is the expected value; the second and third cumulants are respectively the second and third central moments ( the second central moment is the variance ); but the higher cumulants are neither moments nor central moments, but rather more complicated polynomial functions of the moments.
47.
If the points represent probability density, then the zeroth moment is the total probability ( i . e . one ), the first moment is the mean, the second central moment is the variance, the third central moment is the skewness, and the fourth central moment ( with normalization and shift ) is the kurtosis.
48.
If the points represent probability density, then the zeroth moment is the total probability ( i . e . one ), the first moment is the mean, the second central moment is the variance, the third central moment is the skewness, and the fourth central moment ( with normalization and shift ) is the kurtosis.
49.
If the points represent probability density, then the zeroth moment is the total probability ( i . e . one ), the first moment is the mean, the second central moment is the variance, the third central moment is the skewness, and the fourth central moment ( with normalization and shift ) is the kurtosis.
50.
This linearity property does not hold for moments beyond the first raw moment ( the mean ) and the second central moment ( the covariance ), so it is not generally possible to determine the mean and covariance resulting from a nonlinear transformation because the result depends on all the moments, and only the first two are given.
