Causal Relationship

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A Causal Relationship is a asymmetric physical relationship between an event (a causing event) and a mandatory effect (a caused effect) in the world.



References

2024

  • (Wikipedia, 2024) ⇒ https://en.wikipedia.org/wiki/Causality Retrieved:2024-1-19.
    • Causality is an influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is partly responsible for the effect, and the effect is partly dependent on the cause. In general, a process has many causes, [1] which are also said to be causal factors for it, and all lie in its past. An effect can in turn be a cause of, or causal factor for, many other effects, which all lie in its future. Some writers have held that causality is metaphysically prior to notions of time and space.[2] [3] [4] Causality is an abstraction that indicates how the world progresses. As such a basic concept, it is more apt as an explanation of other concepts of progression than as something to be explained by others more basic. The concept is like those of agency and efficacy. For this reason, a leap of intuition may be needed to grasp it. [5] [6] Accordingly, causality is implicit in the logic and structure of ordinary language, as well as explicit in the language of scientific causal notation.

      In English studies of Aristotelian philosophy, the word "cause" is used as a specialized technical term, the translation of Aristotle's term αἰτία, by which Aristotle meant "explanation" or "answer to a 'why' question". Aristotle categorized the four types of answers as material, formal, efficient, and final "causes". In this case, the "cause" is the explanans for the explanandum, and failure to recognize that different kinds of "cause" are being considered can lead to futile debate. Of Aristotle's four explanatory modes, the one nearest to the concerns of the present article is the "efficient" one.

      David Hume, as part of his opposition to rationalism, argued that pure reason alone cannot prove the reality of efficient causality; instead, he appealed to custom and mental habit, observing that all human knowledge derives solely from experience.

      The topic of causality remains a staple in contemporary philosophy.

  1. Compare:
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  5. Whitehead, A.N. (1929). Process and Reality. An Essay in Cosmology. Gifford Lectures Delivered in the University of Edinburgh During the Session 1927–1928, Macmillan, New York; Cambridge University Press, Cambridge UK, "The sole appeal is to intuition."
  6. Cite error: Invalid <ref> tag; no text was provided for refs named Cheng1997

2018

  • (Pearl & Mackenzie, 2018) ⇒ Judea Pearl, and Dana Mackenzie. (2018). “The Book of Why: The New Science of Cause and Effect.” Hachette UK. ISBN:9780465097609
    • QUOTE: … it is important to understand the achievements that causal inference has tallied thus far. We will explore the way that it has transformed the thinking of scientists in almost every data-informed discipline and how it is about to change our lives.
    • The new science addresses seemingly straightforward questions like these:
      • How effective is a given treatment in preventing a disease?
      • Did the new tax law cause our sales to go up, or was it our advertising campaign?
      • What is the health-care cost attributable to obesity?
      • Can hiring records prove an employer is guilty of a policy of sex discrimination?
      • I’m about to quit my job. Should I?
    • These questions have in common a concern with cause-and-effect relationships, recognizable through words such as “preventing,” “cause,” “attributable to,” “policy,” and “should I.” Such words are common in everyday language, and our society constantly demands answers to such questions. Yet, until very recently, science gave us no means even to articulate, let alone answer, them. …

2014

  • (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/causality Retrieved:2014-7-27.
    • Causality (also referred to as causation [1] ) is the relation between an event (the cause) and a second event (the effect), where the second event is understood as a physical consequence of the first. ...
  1. 'The action of causing; the relation of cause and effect' OED

2012

  • (Pearl, 2012) ⇒ Judea Pearl. (2012). “Q&A: A Sure Thing". Interview in Communications of the ACM, 55(6). doi:10.1145/2184319.2184347
    • QUOTE: There are three levels of causal relationships. The zero level, which is the level of associations, not causation, deals with the question “What is?” The second level is “What if?” And the third level is “Why?” That’s the counterfactual level. Initially, I thought of counterfactuals as something for philosophers to deal with. Now I see them as just the opposite. They are the building blocks of scientific understanding.

2011

2009

2007

2006

2000

  • (Pearl, 2000) ⇒ Judea Pearl. (2000). “Causality: Models, reasoning, and inference." Cambridge University Press, ISBN:0521773628
    • QUOTE: … this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. 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, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.