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Standard deviation

Syntax

Definition

There are two common textbook definitions for the standard deviation s of a data vector X:


where

and n is the number of elements in the sample. The two forms of the equation differ only in versus in the divisor.

Description

s = std(X), where X is a vector, returns the standard deviation using (1) above. If X is a random sample of data from a normal distribution, s2 is the best unbiased estimate of its variance.

If X is a matrix, std(X) returns a row vector containing the standard deviation of the elements of each column of X. If X is a multidimensional array, std(X) is the standard deviation of th elements along the first nonsingleton dimension of X.

s = std(X,flag) for flag = 0, is the same as std(X). For flag = 1, std(X,1) returns the standard deviation using (2) above, producing the second moment of the sample about its mean.

s = std(X,flag,dim) computes the standard deviations along the dimension of X specified by scalar dim.

Examples

For matrix X

See Also

corrcoef, cov, mean, median



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