Function variance #

Compute the variance of a matrix or a list with values. In case of a multidimensional array or matrix, the variance over all elements will be calculated.

Additionally, it is possible to compute the variance along the rows or columns of a matrix by specifying the dimension as the second argument.

Optionally, the type of normalization can be specified as the final parameter. The parameter normalization can be one of the following values:

‘unbiased’ (default) The sum of squared errors is divided by (n - 1)
‘uncorrected’ The sum of squared errors is divided by n
‘biased’ The sum of squared errors is divided by (n + 1)

Note that older browser may not like the variable name var. In that case, the function can be called as math['var'](...) instead of math.var(...).

Syntax #

math.variance(a, b, c, ...)
math.variance(A)
math.variance(A, normalization)
math.variance(A, dimension)
math.variance(A, dimension, normalization)

Parameters #

Parameter	Type	Description
`array`	Array \| Matrix	A single matrix or or multiple scalar values
`normalization`	string	Determines how to normalize the variance. Choose ‘unbiased’ (default), ‘uncorrected’, or ‘biased’. Default value: ‘unbiased’.

Returns #

Type	Description
*	The variance

Throws #

Type | Description —- | ———–

Examples #

math.variance(2, 4, 6)                     // returns 4
math.variance([2, 4, 6, 8])                // returns 6.666666666666667
math.variance([2, 4, 6, 8], 'uncorrected') // returns 5
math.variance([2, 4, 6, 8], 'biased')      // returns 4

math.variance([[1, 2, 3], [4, 5, 6]])      // returns 3.5
math.variance([[1, 2, 3], [4, 6, 8]], 0)   // returns [4.5, 8, 12.5]
math.variance([[1, 2, 3], [4, 6, 8]], 1)   // returns [1, 4]
math.variance([[1, 2, 3], [4, 6, 8]], 1, 'biased') // returns [0.5, 2]