2.2 KiB
2.2 KiB
Function variance
Compute the variance of a matrix or a list with values. In case of a (multi dimensional) 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]