Introduction:
The statistics module in Python provides various functions for mathematical statistics and data analysis. It offers a convenient way to perform statistical calculations on numerical data. Below are some of the important functions available in the statistics module:
- Mean Calculation: 
 The- mean()function calculates the arithmetic mean of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 mean_value = statistics.mean(data)
 print("Mean:", mean_value)
- Median Calculation: 
 The- median()function calculates the median of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 median_value = statistics.median(data)
 print("Median:", median_value)
- Mode Calculation: 
 The- mode()function calculates the mode(s) of a list of numbers.python- import statistics
 data = [2, 4, 6, 4, 8, 10, 4]
 mode_values = statistics.mode(data)
 print("Mode:", mode_values)
- Standard Deviation: 
 The- stdev()function calculates the standard deviation of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 stdev_value = statistics.stdev(data)
 print("Standard Deviation:", stdev_value)
- Variance: 
 The- variance()function calculates the variance of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 variance_value = statistics.variance(data)
 print("Variance:", variance_value)
- Harmonic Mean: 
 The- harmonic_mean()function calculates the harmonic mean of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 harmonic_mean_value = statistics.harmonic_mean(data)
 print("Harmonic Mean:", harmonic_mean_value)
- Quantiles: 
 The- quantiles()function calculates the specified quantiles of a list of numbers.python- import statistics
 data = [2, 4, 6, 8, 10]
 quantiles_values = statistics.quantiles(data, n=4)
 print("Quantiles:", quantiles_values)
These functions enable Python programmers to perform a wide range of statistical computations efficiently and accurately on datasets.
 
 
 
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