There are a lot of events in life that we just can’t predict, but just because something is random doesn’t mean we don’t know or can’t learn anything about it. Today, we’re going to talk about how we can extract information from seemingly random events starting with the expected value or mean of a distribution and walking through the first four “moments” – the mean, variance, skewness, and kurtosis.
Note: There are many formulas to calculate skewness and kurtosis (https://www.itl.nist.gov/div898/handbook/eda/section3/eda35b.htm), our formulas deal with what they have in common, their moment generating functions.
More on sheep study: http://aiweirdness.com/post/171451900302/do-neural-nets-dream-of-electric-sheep
More on fecal matter study: http://aem.asm.org/content/early/2018/02/05/AEM.00044-18.abstract
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