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Video lecture by Ken Long (at the Statistics Problem Solvers blog) on Nassim Taleb‘s 4th Quadrant problems [1,2], i.e. a region where statistics not only don’t work but in which statistics are downright dangerous, because they lead you to make predictions as well as control systems that are unprepared for the kinds of systems shocks awaiting you.

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).”, Nassim Taleb, in [1].

[1] Nassim Nicholas Taleb, “The Fourth Quadrant: A Map of the Limits of Statistics“, An Edge Original Essay, Set., 2008. (link)

[2] Nassim Nicholas Taleb,”Convexity, Robustness, and Model Error inside the Fourth Quadrant“, Oxford Lecture (Draft version), Oxford, July 2010. [PDF paper]

Video -“Sand, sand, pile of sand” by Robert Proch (2009) – Impression without an idea, about trying to catch one (music by Pinkfreud).

Complex Adaptive Systems (CAS) are dynamic developing systems which arrange themselves according to external influences and to their own inner current state. If you are familiar with Conway’s “Game of Life“, you have an example of such a system. Complex adaptive systems arrange themselves around one or more critical factors (like in a sandpile, for example, where the pile will rearrange itself when you drop additional sand grains onto it). The theory behind these systems is related to chaos theory, but the systems are said to be “on the edge of chaos“, because they have the ability to adjust themselves (around the critical factors), unlike truly chaotic systems. One interesting thing with CA-systems is that they can suddenly rearrange themselves rather violently or criticality. Like in a sandpile which has a grain added to it, which topples onto other grains, which in turn topple onto other grains, etc. In physics, the Bak-Tang-Wiesenfeld sandpile model is the first discovered example of a dynamical system displaying self-organized criticality and is named after Per Bak [1] [2] [3], Chao Tang [1] [2] and Kurt Wiesenfeld [1] [2]. While running the model, you soon then have an avalanche effect and signatures produced equivalent to those found in nature. In fact, many phenomena in daily life are complex adaptive systems, like weather, traffic, earthquakes, eco-systems, or the stock market, and many of them share this precise 1/f noise pattern. As our brains.

[1] Per Bak, Chao Tang and Kurt Wiesenfeld (1987). “Self-organized criticality: an explanation of 1/f noise“. Physical Review Letters 59: pp. 381-384.
[2] Per Bak, Chao Tang and Kurt Wiesenfeld (1988). “Self-organized criticality“. Physical Review A 38: pp. 364-374.
[3] Per Bak (1996). How Nature Works: The Science of Self-Organized Criticality. New York: Copernicus. ISBN 0-387-94791-4.

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

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