In [1]:

    

import statistics
import math


    

In [2]:

    

l = [10, 1, 3, 7, 1]


    

In [3]:

    

mean = statistics.mean(l)
print(mean)


    

    




4.4

In [4]:

    

my_mean = sum(l) / len(l)
print(my_mean)


    

    




4.4

In [5]:

    

harmonic_mean = statistics.harmonic_mean(l)
print(harmonic_mean)


    

    




1.9408502772643252

In [6]:

    

my_harmonic_mean = len(l) / sum(1 / x for x in l)
print(my_harmonic_mean)


    

    




1.9408502772643255

In [7]:

    

median = statistics.median(l)
print(median)


    

    




3

In [8]:

    

l_even = [10, 1, 3, 7, 1, 6]


    

In [9]:

    

median = statistics.median(l_even)
print(median)


    

    




4.5

In [10]:

    

median_low = statistics.median_low(l_even)
print(median_low)


    

    




3

In [11]:

    

median_high = statistics.median_high(l_even)
print(median_high)


    

    




6

In [12]:

    

print(statistics.median_high(l) == statistics.median_low(l) == statistics.median(l))


    

    




True

In [13]:

    

mode = statistics.mode(l)
print(mode)


    

    




1

In [14]:

    

l_mode_error = [1, 2, 3, 4, 5]

# mode = statistics.mode(l_mode_error)
# StatisticsError: no unique mode; found 5 equally common values


    

In [15]:

    

l_mode_error = [1, 1, 1, 2, 2, 2, 3]

# mode = statistics.mode(l_mode_error)
# StatisticsError: no unique mode; found 2 equally common values


    

In [16]:

    

pvariance = statistics.pvariance(l)
print(pvariance)


    

    




12.64

In [17]:

    

my_pvariance = sum((x - sum(l) / len(l))**2 for x in l) / len(l)
print(my_pvariance)


    

    




12.64

In [18]:

    

pstdev = statistics.pstdev(l)
print(pstdev)


    

    




3.5552777669262356

In [19]:

    

print(math.sqrt(pvariance))


    

    




3.5552777669262356

In [20]:

    

variance = statistics.variance(l)
print(variance)


    

    




15.8

In [21]:

    

my_variance = sum((x - sum(l) / len(l))**2 for x in l) / (len(l) - 1)
print(my_variance)


    

    




15.8

In [22]:

    

stdev = statistics.stdev(l)
print(stdev)


    

    




3.9749213828703582

In [23]:

    

print(math.sqrt(variance))


    

    




3.9749213828703582