Table of Contents

Chapter 5

Monday, 1 January 0001
1-minute read
101 words

Standard Deviation

By definition, the standard deviation $s$ is known as the square root of the variance $s^2$ of a dataset.

\[ s^2 = \frac{\Sigma(x - \bar{x})^2}{n - 1} \]

import math

data = [ 5, 11, 12, 17, 22 ]

def mean():
    sum_of_list = 0
    for x in data:
        sum_of_list += x
    return sum_of_list / len(data)

def std_dev():
    sigma = 0
    mean_of_data = mean()
    for x in data:
        sigma += pow(x - mean_of_data, 2)
    return math.sqrt(sigma / (len(data) - 1))

return "The mean is {}; the standard deviation is {}".format(mean(), std_dev())
The mean is 13.4; the standard deviation is 6.4265076052238514