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Deviants in a normal world

It's definitely been a bit since I've seen this graphy. Anyone who has learnt about standard deviation knows this graph.

Standard Deviation

Standard deviation shows us how spread out all the values in a set are from the mean. The higher the standard deviation, the more spread out the values are over a wider range and the flatter this curve. In a normal distribution, most values are within 1 standard deviation from the mean(the green part of the graph). Apparently NumPy can calculate standard deviation too!

import numpy
numSet = [ *lots of numbers* ]
numSetStdDev = numpy.std(numSet)

Variance

The variance also indicates how spread out the values in a set are. It measures the average degree to which each value differs from the mean.
variance = standard deviation ^2

import numpy
numSet = [ *lots of numbers * ]
numSetVar = numpy.var(numSet)


Source: https://www.w3schools.com/python/python_ml_standard_deviation.asp



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