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Whereas the fundamental laws of physics were regarded as strictly deterministic until the early twentieth century, developments in modern physics have led many physicists to conclude that such determinism is not valid and that the basic laws are statistical in nature. In Causality and Chance in Modern Physics, Professor Bohm criticizes these notions. He argues that determinism and statistical ‘laws o chance’ are two inseparable sides of a single, deeper and more comprehensive structure of law, going beyond either of them. In support of this notion, a new interpretation of the quantum theory is given, based on the assumption of such a structure, in the form of a sub-quantum mechanical level which has both new kinds of causal laws and new kinds of statistical fluctuations. This approach makes possible further insight into the meaning of the quantum theory and suggests ways of extending the theory in new directions. The notion of an inseparable union of statistical and causal aspects is then extended to the whole field of natural law. This work has been unavailable for some years, and for this new edition Professor Bohm has written a fresh introduction which considers developments (such as the recent experiments of Aspect in Paris) which have taken place since it first appeared.

Causality and Chance in Modern Physics by David Bohm – eBook Details

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  • Full Book Name: Causality and Chance in Modern Physics
  • Author Name: David Bohm
  • Book Genre: Philosophy, Physics, Science
  • ISBN # 9780812210026
  • Edition Language: English
  • Date of Publication: 1971-1-1
  • PDF / EPUB File Name: Causality_n_Chance_in_Modern_Physics_-_David_Bohm.pdf, Causality_n_Chance_in_Modern_Physics_-_David_Bohm.epub
  • PDF File Size: 1.2 MB
  • EPUB File Size: 392 KB

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The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence .

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Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence,...

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