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Section: Elementary Functions
Computes the variance of an array along a given dimension. The general syntax for its use is
y = var(x,d)
 where x is an n-dimensions array of numerical type. The output is of the same numerical type as the input. The argument d is optional, and denotes the dimension along which to take the variance. The output y is the same size as x, except that it is singular along the mean direction. So, for example, if x is a 3 x 3 x 4 array, and we compute the mean along dimension d=2, then the output is of size 3 x 1 x 4. 
The output is computed via
![\[ y(m_1,\ldots,m_{d-1},1,m_{d+1},\ldots,m_{p}) = \frac{1}{N-1} \sum_{k=1}^{N} \left(x(m_1,\ldots,m_{d-1},k,m_{d+1},\ldots,m_{p}) - \bar{x}\right)^2, \]](form_28.png) 
where
![\[ \bar{x} = \frac{1}{N} \sum_{k=1}^{N} x(m_1,\ldots,m_{d-1},k,m_{d+1},\ldots,m_{p}) \]](form_29.png) 
 If d is omitted, then the mean is taken along the first non-singleton dimension of x. 
The following piece of code demonstrates various uses of the var function
--> A = [5,1,3;3,2,1;0,3,1] A = 5 1 3 3 2 1 0 3 1
We start by calling var without a dimension argument, in which case it defaults to the first nonsingular dimension (in this case, along the columns or d = 1).
--> var(A)
ans = 
    6.3333    1.0000    1.3333 
Next, we take the variance along the rows.
--> var(A,2)
ans = 
    4.0000 
    1.0000 
    2.3333