“Catching long tail distribution” (Ted Dunning)

One of the best presentations on what can happen if someone takes a naive approach to network data. It also highlights what is, to my mind, the greatly underappreciated t-distribution, which is typically only used in connection with frequentist Student t-tests, but serves as a generator someplace between the Gaussian and the crazy Cauchy distribution. Also relevant is the Lévy flight which has significance in biology. (See also.)

The message is that a combination of multiple paths, sampling rate changes, and a glitch on one of the paths can make an event appear to occur where there is none.

About hypergeometric

See http://www.linkedin.com/in/deepdevelopment/ and http://667-per-cm.net
This entry was posted in Cauchy distribution, complex systems, data science, Lévy flights, leptokurtic, mathematics, maths, networks, physics, population biology, population dynamics, regime shifts, sampling, statistics, Student t distribution, time series. Bookmark the permalink.

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