One of the most common processes that does not fit the normal distribution is that of a power law, whereby one quantity varies with another’s exponent rather than linearly. For example, the Richter scale describes the power of earthquakes on a power-law distribution scale: an 8 is 10x more destructive than a 7, and a 9 is 10x more destructive than an 8. The central limit theorem does not apply and there is thus no “average” earthquake. This is true of all power-law distributions. – Shane Parrish
“A functional relationship between two quantities, where a relative change in one quantity results in a proportional relative change in the other quantity, independent of the initial size of those quantities: one quantity varies as a power of another.” (related: Pareto distribution; Pareto principle — “for many events, roughly 80% of the effects come from 20% of the causes.”, diminishing returns, premature optimization, heavy-tailed distribution, fat-tailed distribution; long tail — “the portion of the distribution having a large number of occurrences far from the “head” or central part of the distribution.”; black swan theory — “a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight.”) – Gabriel Weinberg
Source:
Shane Parrish’s Farnam Street Mental Model Guide
https://www.farnamstreetblog.com/mental-models/
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Gabriel Weinberg’s Mental Models I Find Repeatedly Useful
https://medium.com/@yegg/mental-models-i-find-repeatedly-useful-936f1cc405d
