## GAUSS_PDF

The GAUSS_PDF function computes the probability P that, in a standard Gaussian (normal) distribution with a mean of 0.0 and a variance of 1.0, a random variable X is less than or equal to a user-specified cutoff value V.

This routine is written in the IDL language. Its source code can be found in the file `gauss_pdf.pro` in the `lib` subdirectory of the IDL distribution.

### Syntax

Result = GAUSS_PDF(V)

### Return Value

This function returns a scalar or array with the same dimensions as V. If V is double-precision, the result is double-precision, otherwise the result is single-precision.

### Arguments

#### V

A scalar or array that specifies the cutoff value(s).

None.

### Examples

#### Example 1

Compute the probability that a random variable X, from the standard Gaussian (normal) distribution, is less than or equal to 2.44:

```PRINT, GAUSS_PDF(2.44)
```

IDL Prints:

```0.992656
```

#### Example 2

Compute the probability that a random variable X, from the standard Gaussian (normal) distribution, is less than or equal to 10.0 and greater than or equal to 2.0:

```PRINT, GAUSS_PDF(10.0) - GAUSS_PDF(2.0)
```

IDL Prints:

```0.0227501
```

#### Example 3

Compute the probability that a random variable X, from the Gaussian (normal) distribution with a mean of 0.8 and a variance of 4.0, is less than or equal to 2.44:

```PRINT, GAUSS_PDF( (2.44 - 0.80)/SQRT(4.0) )
```

IDL Prints:

```0.793892
```

Introduced: 4.0