Python statistics.pstdev() Method with Examples

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statistics.pstdev() Method in Python:

The statistics.pstdev() method computes the standard deviation from a population as a whole.

The standard deviation measures how evenly distributed the numbers are.

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

Tip: Unlike variance, the standard deviation is expressed in the same units as the data.

Tip: The standard deviation is equal to the square root of the sample variance.

Look at the statistics.stdev() method to calculate the standard deviation from a sample of data.

Syntax:

statistics.pstdev(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 float value representing the given data’s population standard deviation.

Examples:

Example1:

Input:

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

Output:

The standard deviation of the given list items [10, 20, 40, 15, 30] =  10.770329614269007

Example2:

Input:

Given list = [3, 4, 5, 1, 3, 2]

Output:

The standard deviation of the given list items [3, 4, 5, 1, 3, 2] = 1.2909944487358056

statistics.pstdev() 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.pstdev() method that computes the standard deviation from a population as a whole.
  • Store it in another variable.
  • Print the standard deviation 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.pstdev() method that
# computes the standard deviation from a population as a whole.
# Store it in another variable.
rslt = statistics.pstdev(gvn_lst)
# Print the standard deviation of the given list items.
print("The standard deviation of the given list items", gvn_lst, "= ", rslt)

Output:

The standard deviation of the given list items [10, 20, 40, 15, 30] =  10.770329614269007

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.pstdev() method that computes the standard deviation from a population as a whole.
  • Store it in another variable.
  • Print the standard deviation 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.pstdev() method that
# computes the standard deviation from a population as a whole.
# Store it in another variable.
rslt = statistics.pstdev(gvn_lst)
# Print the standard deviation of the given list items.
print("The standard deviation of the given list items", gvn_lst, "= ", rslt)

Output:

Enter some random List Elements separated by spaces = 3 4 5 1 3 2
The standard deviation of the given list items [3, 4, 5, 1, 3, 2] = 1.2909944487358056