def kurtosis(iterable):
mean = medida_central.mean(iterable)
amount = len(iterable)
sd = standard_deviation(iterable)
total_sum = sum([((value - mean) / sd)**4 for value in iterable])
return (((amount * (amount + 1)) /
((amount - 1) * (amount - 2) *
(amount - 3))) * total_sum) - (3 * ((amount - 1)**2) /
(amount - 2) * (amount - 3))
def skewness(iterable):
mean = medida_central.mean(iterable)
amount = len(iterable)
sd = standard_deviation(iterable)
total_sum = sum([((value - mean) / sd)**3 for value in iterable])
return (amount / ((amount - 1) * (amount - 2))) * total_sum
def population_variance(iterable):
mean = medida_central.mean(iterable)
return sum([(value - mean)**2 for value in iterable]) / len(iterable)
def coefficient_variation(iterable):
return (standard_deviation(iterable) / medida_central.mean(iterable)) * 100
def sample_variance(iterable):
mean = medida_central.mean(iterable)
return sum([(value - mean)**2 for value in iterable]) / (len(iterable) - 1)