# scipy.special.nrdtrisd#

scipy.special.nrdtrisd(mn, p, x, out=None) = <ufunc 'nrdtrisd'>#

Calculate standard deviation of normal distribution given other params.

Parameters:
mnscalar or ndarray

The mean of the normal distribution.

parray_like

CDF values, in range (0, 1].

xarray_like

Quantiles, i.e. the upper limit of integration.

outndarray, optional

Optional output array for the function results

Returns:
stdscalar or ndarray

Standard deviation.

`scipy.stats.norm`

Normal distribution

`ndtr`

Standard normal cumulative probability distribution

`ndtri`

Inverse of standard normal CDF with respect to quantile

`nrdtrimn`

Inverse of normal distribution CDF with respect to mean

Examples

`nrdtrisd` can be used to recover the standard deviation of a normal distribution if we know the CDF value p for a given quantile x and the mean mn. First, we calculate the normal distribution CDF for an exemplary parameter set.

```>>> from scipy.stats import norm
>>> mean = 3.
>>> std = 2.
>>> x = 6.
>>> p = norm.cdf(x, loc=mean, scale=std)
>>> p
0.9331927987311419
```

Verify that `nrdtrisd` returns the original value for std.

```>>> from scipy.special import nrdtrisd
>>> nrdtrisd(mean, p, x)
2.0000000000000004
```