Bigger than Chaos: Understanding Complexity through Probability
Language: English
Published by Harvard University Press, 2006
- Softcover
- Used

Seller: WorldofBooks, Goring-By-Sea, WS, United KingdomWorldofBooks
AbeBooks seller since March 16, 2007
Condition: Used - Very good
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Add to basketItem description from seller
The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Seller Inventory # GOR013555589
- Title
- Bigger than Chaos: Understanding Complexity through Probability
- Author
- Strevens, Michael
- Publisher
- Harvard University Press
- Publication year
- 2006
- Condition
- Very Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0674022599
- ISBN 13
- 9780674022591
- Item weight
- 585 grams
Many complex systems―from immensely complicated ecosystems to minute assemblages of molecules―surprise us with their simple behavior. Consider, for instance, the snowflake, in which a great number of water molecules arrange themselves in patterns with six-way symmetry. How is it that molecules moving seemingly at random become organized according to the simple, six-fold rule? How do the comings, goings, meetings, and eatings of individual animals add up to the simple dynamics of ecosystem populations? More generally, how does complex and seemingly capricious microbehavior generate stable, predictable macrobehavior?
In this book, Michael Strevens aims to explain how simplicity can coexist with, indeed be caused by, the tangled interconnections between a complex system’s many parts. At the center of Strevens’s explanation is the notion of probability and, more particularly, probabilistic independence. By examining the foundations of statistical reasoning about complex systems such as gases, ecosystems, and certain social systems, Strevens provides an understanding of how simplicity emerges from complexity. Along the way, he draws lessons concerning the low-level explanation of high-level phenomena and the basis for introducing probabilistic concepts into physical theory.
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WorldofBooks
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