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