MATLAB Function Reference |

**Syntax**

**Definition**

There are two common textbook definitions for the standard deviation `s`

of a data vector `X`

.

and 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. The result `s`

is the square root of an unbiased estimator of the variance of the population from which `X`

is drawn, as long as `X`

consists of independent, identically distributed samples.

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 the 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`

. Set `flag`

to `0`

to normalize `Y`

by *n*-1; set `flag`

to `1`

to normalize by *n*.

**Examples**

**See Also**

`corrcoef`

, `cov`

, `mean`

, `median`

, `var`

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