# Function std

Compute the standard deviation of a matrix or a list with values. The standard deviations is defined as the square root of the variance: `std(A) = sqrt(var(A))`. In case of a (multi dimensional) array or matrix, the standard deviation over all elements will be calculated.

Optionally, the type of normalization can be specified as second 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)

## Syntax

``````std(a, b, c, ...)
std(A)
std(A, 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 standard deviation

## Examples

``````std(2, 4, 6);                     // returns 2
std([2, 4, 6, 8]);                // returns 2.581988897471611
std([2, 4, 6, 8], 'uncorrected'); // returns 2.23606797749979
std([2, 4, 6, 8], 'biased');      // returns 2

std([[1, 2, 3], [4, 5, 6]]);      // returns 1.8708286933869707
``````