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Справка Scilab >> Statistics > Data with Missing Values > nanstdev

# nanstdev

standard deviation (ignoring the NANs).

### Syntax

```s=nanstdev(x)
s=nanstdev(x,'r') or m=nanstdev(x,1)
s=nanstdev(x,'c') or m=nanstdev(x,2)```

### Arguments

x

real or complex vector or matrix

### Description

This function computes the standard deviation of the values of a vector or matrix `x` (ignoring the NANs).

For a vector or a matrix `x`, `s=nanstdev(x)` returns in the scalar `s` the standard deviation of all the entries of `x` (ignoring the NANs).

`s=nanstdev(x,'r')` (or, equivalently, `s=nanstdev(x,1)`) is the rowwise standard deviation. It returns in each entry of the row vector `s` the standard deviation of each column of `x` (ignoring the NANs).

`s=nanstdev(x,'c')` (or, equivalently, `s=nanstdev(x,2)`) is the columnwise standard deviation. It returns in each entry of the column vector `s` the standard deviation of each row of `x` (ignoring the NANs).

In Labostat, NAN values stand for missing values in tables.

### Examples

```x=[0.2113249 0.0002211 0.6653811;
0.7560439 %nan      0.6283918;
0.3       0.2       0.5      ];
s=nanstdev(x)
s=nanstdev(x,'r')
s=nanstdev(x,'c')```

### Bibliography

Wonacott, T.H. & Wonacott, R.J.; Introductory Statistics, fifth edition, J.Wiley & Sons, 1990.

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