# 
#  Overview
The **`gauss`** method is used to get a floating value chosen from a Gaussian or normal distribution with the given mean and standard deviation.

##
## What is Gaussian or normal distribution?

The **Gaussian distribution**, also known as the normal distribution, is a symmetric probability distribution centered on the mean, indicating that data near the mean occur more frequently than data far from it. The normal distribution will appear as a bell curve on a graph. The following image shows what a bell curve looks like when plotted on a graph.


<center>

![](/api/edpresso/shot/5772673530986496/image/4725499288354816)

<center>


# 
#  Syntax

---

```python
random.gauss(mu, sigma)
```

---

# 
## Parameters 

- **`mu`**: The mean value.
- **`sigma`**: The standard deviation value.


##
## Return value

This method returns a floating-point value.

import random

mu = 5
sigma = 3.4
val = random.gauss(mu, sigma=sigma)

print("random.gauss(%s, %s) = %s" % (mu, sigma, val))

# 
## Code explanation

- Line 1: We import the `random` module.
- Line 3: We define the mean value `mu`.
- Line 4: We define the standard deviation value `sigma`.
- Line 5: We store the value returned by `gauss(mu,sigma)` in the variable `val`.
- Line 7: We print `val` to the console.


What is the random.gauss() method in Python?

Generates a Gaussian-distributed float with specified mean and standard deviation using random.gauss().