**statistics.pvariance() Method in Python:**

The statistics.pvariance() method computes the variance of a whole population.

A high variance indicates that the data is dispersed, whereas a low variance indicates that the data is tightly clustered around the mean.

Examine the statistics.variance() method to determine the variance from a sample of data.

**Syntax:**

statistics.pvariance(data, xbar)

**Parameters**

**data:** This is Required. It is the data values that will be used (it can be any sequence, list, or iterator).

**xbar:** This is Optional. The arithmetic mean of the given data (can also be a second moment around a point that is not the mean). If omitted (or set to None), the mean is calculated automatically.

**Note:** It is important to note that if the data is empty, it returns a StatisticsError.

**Return Value:**

Returns a Â float value representing the given data’s population variance.

**Examples:**

**Example1:**

**Input:**

Given list = [10, 20, 40, 15, 30]

**Output:**

The variance of the given list items [10, 20, 40, 15, 30] = 116

**Example2:**

**Input:**

Given list = [1, 6, 9, 7]

**Output:**

The variance of the given list items [1, 6, 9, 7] = 8.6875

statistics.pvariance() Method with Examples in Python

### Method #1: Using Built-in Functions (Static Input)

**Approach:**

- Import statistics module using the import keyword.
- Give the list as static input and store it in a variable.
- Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.
- Store it in another variable.
- Print the variance of the given list items.
- The Exit of the Program.

**Below is the implementation:**

# Import statistics module using the import keyword. import statistics # Give the list as static input and store it in a variable. gvn_lst = [10, 20, 40, 15, 30] # Pass the given list as an argument to the statistics.pvariance() method that # computes the variance of a whole population. # Store it in another variable. rslt = statistics.pvariance(gvn_lst) # Print the variance of the given list items. print("The variance of the given list items", gvn_lst, "= ", rslt)

**Output:**

The variance of the given list items [10, 20, 40, 15, 30] = 116

### Method #2: Using Built-in Functions (User Input)

**Approach:**

- Import statistics module using the import keyword.
- Give the list as user input using list(),map(),input(),and split() functions.
- Store it in another variable.
- Pass the given list as an argument to the statistics.pvariance() method that computes the variance of a whole population.
- Store it in another variable.
- Print the variance of the given list items.
- The Exit of the Program.

**Below is the implementation:**

# Import statistics module using the import keyword. import statistics # Give the list as user input using list(),map(),input(),and split() functions. # Store it in a variable. gvn_lst = list(map(int, input( 'Enter some random List Elements separated by spaces = ').split())) # Pass the given list as an argument to the statistics.pvariance() method that # computes the variance of a whole population. # Store it in another variable. rslt = statistics.pvariance(gvn_lst) # Print the variance of the given list items. print("The variance of the given list items", gvn_lst, "= ", rslt)

**Output:**

Enter some random List Elements separated by spaces = 1 6 9 7 The variance of the given list items [1, 6, 9, 7] = 8.6875