## Chaos: A Very Short IntroductionChaos exists in systems all around us. Even the simplest system of cause and effect can be subject to chaos, denying us accurate predictions of its behaviour, and sometimes giving rise to astonishing structures of large-scale order. Our growing understanding of Chaos Theory is having fascinating applications in the real world - from technology to global warming, politics, human behaviour, and even gambling on the stock market. Leonard Smith shows that we all have an intuitive understanding of chaotic systems. He uses accessible maths and physics (replacing complex equations with simple examples like pendulums, railway lines, and tossing coins) to explain the theory, and points to numerous examples in philosophy and literature (Edgar Allen Poe, Chang-Tzu, Arthur Conan Doyle) that illuminate the problems. The beauty of fractal patterns and their relation to chaos, as well as the history of chaos, and its uses in the real world and implications for the philosophy of science are all discussed in this Very Short Introduction. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |

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Procura do Utilizador - qebo - LibraryThingI'm not sure this one truly counts as read. If read is each sentence from cover to cover, then yes. I read is comprehended well enough to pass a test, then no. The trouble isn't with the book itself ... Ler crítica na íntegra

### Índice

1 | |

2 Exponential growth nonlinearity common sense | 22 |

determinism randomness and noise | 33 |

4 Chaos in mathematical models | 58 |

5 Fractals strange attractors and dimensions | 76 |

6 Quantifying the dynamics of uncertainty | 87 |

7 Real numbers real observations and computers | 104 |

statistics and chaos | 112 |

does chaos constrain our forecasts? | 123 |

can we see through our models? | 132 |

11 Philosophy in chaos | 154 |

Glossary | 163 |

Further reading | 169 |

Index | 173 |

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### Palavras e frases frequentes

21st-century demon Apprentice Map attractor average Baker’s Map behaviour bell-shaped distribution best models bits butterfly effect chaotic systems climate models components computer simulations Day storm decision support define digital computer dimension dynamical system Earth’s ECMWF ensemble forecast ensemble members equations error exponential growth fact fractal Full Logistic Map future Galton Board golf balls Hénon Hénon Map impact infinitesimal initial condition insight iteration least squares look Lorenz Lyapunov exponent mathematical chaos mathematical map mathematical models mathematical systems mathematicians mature pair measure model inadequacy Moore-Spiegel NAG Board nonlinear systems number of rabbits observational noise panel parameter values perfect model periodic loop physical systems physicist population predictability probability forecasts quantify question random number real world reflect scientists self-similar sensitive dependence shadow solar space statistician statistics stochastic study of chaos temperature Tent Map Theorem things today’s trajectory voles weather forecasting weather model zero