Causal Analytics and Risk Analytics

Louis Anthony Cox, Douglas A. Popken and Richard X. Sun
Additional contact information
Louis Anthony Cox: Cox Associates
Douglas A. Popken: Cox Associates
Richard X. Sun: Cox Associates

Chapter Chapter 1 in Causal Analytics for Applied Risk Analysis, 2018, pp 3-95 from Springer

Abstract: Abstract Countless books and articles on data science and analytics discuss descriptive analytics, predictive analytics, and prescriptive analytics. An additional analytics area that is much less discussed links this world of analytics, with its statistical model-based descriptions and predictions, to the world of practical decisions in which actions have consequences that decision-makers, and perhaps other stake-holders, care about, and about which they are often uncertain. This is the area of causal analytics. How causal analytics relates to other analytics areas and how its methods can be used to predict what to expect next, explain past outcomes and observations, prescribe what to do next to improve future outcomes, and evaluate how well past or current policies accomplish their intended goals—for whom, and under what conditions—are the main topics of this book.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-78242-3_1

Ordering information: This item can be ordered from
http://www.springer.com/9783319782423

DOI: 10.1007/978-3-319-78242-3_1

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().