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:

Syntax #

math.std(a, b, c, ...)
math.std(A)
math.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 #

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

math.std([[1, 2, 3], [4, 5, 6]])      // returns 1.8708286933869707

See also #

mean, median, max, min, prod, sum, var

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