Skewness

`y = skewness(X)`

y = skewness(X,flag)

y = skewness(X,flag,dim)

`y = skewness(X)`

returns the
sample skewness of `X`

. For vectors, `skewness(x)`

is
the skewness of the elements of `x`

. For matrices, `skewness(X)`

is
a row vector containing the sample skewness of each column. For N-dimensional
arrays, `skewness`

operates along the first nonsingleton
dimension of `X`

.

`y = skewness(X,flag)`

specifies
whether to correct for bias (`flag = 0`

)
or not (`flag = 1`

,
the default). When `X`

represents a sample from a
population, the skewness of `X`

is biased; that is,
it will tend to differ from the population skewness by a systematic
amount that depends on the size of the sample. You can set `flag = 0`

to correct for this systematic
bias.

`y = skewness(X,flag,dim)`

takes the skewness
along dimension `dim`

of `X`

.

`skewness`

treats `NaN`

s as
missing values and removes them.

X = randn([5 4]) X = 1.1650 1.6961 -1.4462 -0.3600 0.6268 0.0591 -0.7012 -0.1356 0.0751 1.7971 1.2460 -1.3493 0.3516 0.2641 -0.6390 -1.2704 -0.6965 0.8717 0.5774 0.9846 y = skewness(X) y = -0.2933 0.0482 0.2735 0.4641

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