'''

stats.py

Python module with functions for calculating common statistical measures

'''

from collections import Counter

def mean(numbers):

s = sum(numbers)

N = len(numbers)

mean = s/N

return mean

def median(numbers):

# find the numnber of items

N = len(numbers)

# sort the list in ascending order

numbers.sort()

# find the median

if N % 2 == 0:

# if N is even

m1 = N/2

m2 = (N/2) + 1

# convert to integer, match position

m1 = int(m1) - 1

m2 = int(m2) - 1

median = (numbers[m1] + numbers[m2])/2

else:

m = (N+1)/2

# convert to integer, match position

m = int(m) - 1

median = numbers[m]

return median

def mode(numbers):

c = Counter(numbers)

mode = c.most_common(1)

return mode[0][0]

def find_differences(numbers):

m = mean(numbers)

# find the differences from the mean

diff = []

for num in numbers:

diff.append(num-m)

return diff

def variance_sd(numbers):

# find the list of differences

diff = find_differences(numbers)

# find the squared differences

squared_diff = []

for d in diff:

squared_diff.append(d**2)

# find the variance

sum_squared_diff = sum(squared_diff)

variance = sum_squared_diff/len(numbers)

return variance, variance**0.5