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Causal Analytics for Applied Risk Analysis

  • Louis Anthony Cox Jr.
  • Douglas A. Popken
  • Richard X. Sun

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 270)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Concepts and Methods of Causal Analytics

    1. Front Matter
      Pages 1-1
    2. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 3-95
    3. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 97-247
  3. Descriptive Analytics in Public and Occupational Health

    1. Front Matter
      Pages 249-249
    2. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 313-332
  4. Predictive and Causal Analytics

  5. Evaluation Analytics

    1. Front Matter
      Pages 415-415
    2. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 417-442
  6. Risk Management: Insights from Prescriptive, Learning, and Collaborative Analytics

    1. Front Matter
      Pages 455-455
    2. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 493-511
    3. Louis Anthony Cox Jr., Douglas A. Popken, Richard X. Sun
      Pages 513-556
  7. Back Matter
    Pages 583-588

About this book

Introduction

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.

Keywords

Decision Making Risk Analysis Risk Management Risk Models Causal Analytics Risk Analytics Descriptive Analytics Evaluation Analytics Causal Models

Authors and affiliations

  • Louis Anthony Cox Jr.
    • 1
  • Douglas A. Popken
    • 2
  • Richard X. Sun
    • 3
  1. 1.Cox AssociatesDenverUSA
  2. 2.Cox AssociatesLittletonUSA
  3. 3.Cox AssociatesEast BrunswickUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-78242-3
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Business and Management
  • Print ISBN 978-3-319-78240-9
  • Online ISBN 978-3-319-78242-3
  • Series Print ISSN 0884-8289
  • Series Online ISSN 2214-7934
  • Buy this book on publisher's site