Illustrating the Central Limit Theorem Using Python and Numpy

Published: 31 January 2018
on channel: Jeffrey James

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https://gist.github.com/jrjames83/e37...

Using numpy we generate a population distribution with non-normal characteristics (gamma family). Then by way of the random module, we take a series of samples from that distribution, computing their average each time, then plot the distribution of the averages.

The result is that the distribution of the averages is normally distributed. We then observe the mean of the normally distributed averages, is the same as the mean of the Gamma population distribution.

The upshot is that you can leverage known traits of the normal distribution now to make observations about the parent distribution.

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