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Everyday Chaos

- The Mathematics of Unpredictability, from the Weather to the Stock Market
Af: Brian Clegg Engelsk Paperback

Everyday Chaos

- The Mathematics of Unpredictability, from the Weather to the Stock Market
Af: Brian Clegg Engelsk Paperback
Tjek vores konkurrenters priser
Chaos and complexity explained, with illuminating examples ranging from unpredictable pendulums to London''s wobbly Millennium Bridge.

The math we are taught in school is precise and only deals with simple situations. Reality is far more complex. Trying to understand a system with multiple interacting components—the weather, for example, or the human body, or the stock market—means dealing with two factors: chaos and complexity. If we don''t understand these two essential subjects, we can''t understand the real world. In Everyday Chaos, Brian Clegg explains chaos and complexity for the general reader, with an accessible, engaging text and striking full-color illustrations.

By chaos, Clegg means a system where complex interactions make predicting long-term outcomes nearly impossible; complexity means complex interacting systems that have new emergent properties that make them more than the sum of their parts. Clegg illustrates these phenomena with discussions of predictable randomness, the power of probability, and the behavior of pendulums. He describes what Newton got wrong about gravity; how feedback kept steam engines from exploding; and why weather produces chaos. He considers the stock market, politics, bestseller lists, big data, and London''s wobbling Millennium Bridge as examples of chaotic systems, and he explains how a better understanding of chaos helps scientists predict more accurately the risk of catastrophic Earth-asteroid collisions. We learn that our brains are complex, self-organizing systems; that the structure of snowflakes exemplifies emergence; and that life itself has been shown to be an emergent property of a complex system.

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Chaos and complexity explained, with illuminating examples ranging from unpredictable pendulums to London''s wobbly Millennium Bridge.

The math we are taught in school is precise and only deals with simple situations. Reality is far more complex. Trying to understand a system with multiple interacting components—the weather, for example, or the human body, or the stock market—means dealing with two factors: chaos and complexity. If we don''t understand these two essential subjects, we can''t understand the real world. In Everyday Chaos, Brian Clegg explains chaos and complexity for the general reader, with an accessible, engaging text and striking full-color illustrations.

By chaos, Clegg means a system where complex interactions make predicting long-term outcomes nearly impossible; complexity means complex interacting systems that have new emergent properties that make them more than the sum of their parts. Clegg illustrates these phenomena with discussions of predictable randomness, the power of probability, and the behavior of pendulums. He describes what Newton got wrong about gravity; how feedback kept steam engines from exploding; and why weather produces chaos. He considers the stock market, politics, bestseller lists, big data, and London''s wobbling Millennium Bridge as examples of chaotic systems, and he explains how a better understanding of chaos helps scientists predict more accurately the risk of catastrophic Earth-asteroid collisions. We learn that our brains are complex, self-organizing systems; that the structure of snowflakes exemplifies emergence; and that life itself has been shown to be an emergent property of a complex system.

Produktdetaljer
Sprog: Engelsk
Sider: 256
ISBN-13: 9780262539692
Indbinding: Paperback
Udgave:
ISBN-10: 0262539691
Kategori: Talsystemer
Udg. Dato: 6 okt 2020
Længde: 23mm
Bredde: 240mm
Højde: 165mm
Forlag: MIT Press Ltd
Oplagsdato: 6 okt 2020
Forfatter(e): Brian Clegg
Forfatter(e) Brian Clegg


Kategori Talsystemer


ISBN-13 9780262539692


Sprog Engelsk


Indbinding Paperback


Sider 256


Udgave


Længde 23mm


Bredde 240mm


Højde 165mm


Udg. Dato 6 okt 2020


Oplagsdato 6 okt 2020


Forlag MIT Press Ltd

Kategori sammenhænge