#    
## Overview
The **`statistics.variance()`** **method** in Python is used to return the variance of a sample of given data.

This method is unlike the **`statistics.pvariance()`** **method**, which calculates the variance of an entire population.

**Variance** is the sum of the squared distances of each term distribution from the mean of the data, divided by the number of observations, is shown below:



$$S^2 = \frac{\sum (x_i - \bar{x})^2}{n - 1}$$

Where:

$S^{2}$ = variance

$xi$ = value of one observation

$x$ = the mean value of the data

$n$ = the number of observations

#   
#  Syntax
```
statistics.variance(data, xbar)
```
#    
#  Parameter value
|Parameter|Value|
|:----|:----|
|``data``|It is required with real-valued numbers. It can be a list, a sequence, or an iterator.|
|``xbar``|It is required and iterable with real-valued numbers. It can be a list or a sequence.
|
#    
## Return value
The ``statistics.variance()`` method returns a float value, which represents the variance of the given data.

##   
## Example
Let's use the ``statistics.variance()`` method to calculate the variance for the given data.
## 
## Code

import statistics

# creating a data set
data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
# to obtain the variance 
the_variance = statistics.variance(data)
print('The variance is', the_variance)


#    
## Explanation
* **Line 1:** We import the ``statistics`` module.
* **Line 4:** We create a data set called ``data``.
* **Line 6:** We use the ``statistics.variance()`` method to obtain the variance of the ``data`` and assign the value to another variable, `` the_variance``.
* **Line 7:** We print `the_variance`, which contains the variance of the given data.


What is the statistics variance() method in Python?

 Overview The statistics.variance() method in Python is used to return the variance of a sample of given data. This method is unlike the statistics.pvariance() method, which calculates the variance of an entire population. Variance is the sum of the squared distances of each term distribution from the mean of the data, divided by the number of observations, is shown below: 

Parameter	Value
`data`	It is required with real-valued numbers. It can be a list, a sequence, or an iterator.
`xbar`	It is required and iterable with real-valued numbers. It can be a list or a sequence.