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Should We Risk It?

Exploring Environmental, Health, and Technological Problem Solving

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How dangerous is smoking? What are the risks of nuclear power or climate change? How likely is it to die in an airplane accident? Understanding these risks is crucial, yet the demand for skilled risk analysts has outpaced training programs. This book addresses that gap by unifying various theories and methodologies related to risk analysis in health, environmental, and technological contexts. It offers a diverse array of case studies and practical problems, catering to the need for an up-to-date resource for both teaching and self-study. Key topics include order-of-magnitude estimation, dose-response calculations, exposure assessment, and modeling complexities. The authors also delve into fault-tree analysis, uncertainty management, and social theories of risk communication. They cover essential statistics, Monte Carlo methods, Bayesian analysis, and techniques for evaluating uncertainty and forecasts. This comprehensive approach will resonate with professionals in environmental science, healthcare, engineering, and policy-making, all of whom face increasing decisions that require risk and cost/benefit analysis. This work is poised to become a foundational text for courses in risk and decision analysis as well as applied statistics focused on environmental and technological challenges.

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Should We Risk It?, Daniel M. Kammen, David M. Hassenzahl

Lingua
Pubblicato
2001
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(In brossura)
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4,9
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6 Valutazioni

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Titolo
Should We Risk It?
Sottotitolo
Exploring Environmental, Health, and Technological Problem Solving
Lingua
Inglese
Pubblicato
2001
Formato
In brossura
Pagine
404
ISBN10
0691074577
ISBN13
9780691074573
Serie
Valutazione
4,85 su 5
Descrizione
How dangerous is smoking? What are the risks of nuclear power or climate change? How likely is it to die in an airplane accident? Understanding these risks is crucial, yet the demand for skilled risk analysts has outpaced training programs. This book addresses that gap by unifying various theories and methodologies related to risk analysis in health, environmental, and technological contexts. It offers a diverse array of case studies and practical problems, catering to the need for an up-to-date resource for both teaching and self-study. Key topics include order-of-magnitude estimation, dose-response calculations, exposure assessment, and modeling complexities. The authors also delve into fault-tree analysis, uncertainty management, and social theories of risk communication. They cover essential statistics, Monte Carlo methods, Bayesian analysis, and techniques for evaluating uncertainty and forecasts. This comprehensive approach will resonate with professionals in environmental science, healthcare, engineering, and policy-making, all of whom face increasing decisions that require risk and cost/benefit analysis. This work is poised to become a foundational text for courses in risk and decision analysis as well as applied statistics focused on environmental and technological challenges.