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Causal analytics for applied risk an...
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Cox, Louis Anthony.
Causal analytics for applied risk analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Causal analytics for applied risk analysisby Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun.
作者:
Cox, Louis Anthony.
其他作者:
Popken, Douglas A.
出版者:
Cham :Springer International Publishing :2018.
面頁冊數:
xxii, 588 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Risk assessment.
電子資源:
http://dx.doi.org/10.1007/978-3-319-78242-3
ISBN:
9783319782423$q(electronic bk.)
Causal analytics for applied risk analysis
Cox, Louis Anthony.
Causal analytics for applied risk analysis
[electronic resource] /by Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun. - Cham :Springer International Publishing :2018. - xxii, 588 p. :ill., digital ;24 cm. - International series in operations research & management science,v.2700884-8289 ;. - International series in operations research & management science ;v. 140..
Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives. The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
ISBN: 9783319782423$q(electronic bk.)
Standard No.: 10.1007/978-3-319-78242-3doiSubjects--Topical Terms:
182678
Risk assessment.
LC Class. No.: HD61
Dewey Class. No.: 658.155
Causal analytics for applied risk analysis
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Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives. The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
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