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:
Themean()
function calculates the arithmetic mean of a list of numbers.pythonimport statistics
data = [2, 4, 6, 8, 10]
mean_value = statistics.mean(data)
print("Mean:", mean_value)Median Calculation:
Themedian()
function calculates the median of a list of numbers.pythonimport statistics
data = [2, 4, 6, 8, 10]
median_value = statistics.median(data)
print("Median:", median_value)Mode Calculation:
Themode()
function calculates the mode(s) of a list of numbers.pythonimport statistics
data = [2, 4, 6, 4, 8, 10, 4]
mode_values = statistics.mode(data)
print("Mode:", mode_values)Standard Deviation:
Thestdev()
function calculates the standard deviation of a list of numbers.pythonimport statistics
data = [2, 4, 6, 8, 10]
stdev_value = statistics.stdev(data)
print("Standard Deviation:", stdev_value)Variance:
Thevariance()
function calculates the variance of a list of numbers.pythonimport statistics
data = [2, 4, 6, 8, 10]
variance_value = statistics.variance(data)
print("Variance:", variance_value)Harmonic Mean:
Theharmonic_mean()
function calculates the harmonic mean of a list of numbers.pythonimport statistics
data = [2, 4, 6, 8, 10]
harmonic_mean_value = statistics.harmonic_mean(data)
print("Harmonic Mean:", harmonic_mean_value)Quantiles:
Thequantiles()
function calculates the specified quantiles of a list of numbers.pythonimport 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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