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  2. Causal notation - Wikipedia

    en.wikipedia.org/wiki/Causal_notation

    Causal notation is notation used to express cause and effect. In nature and human societies, many phenomena have causal relationships where one phenomenon A (a cause ...

  3. Causal model - Wikipedia

    en.wikipedia.org/wiki/Causal_model

    Comparison of two competing causal models (DCM, GCM) used for interpretation of fMRI images [1] In metaphysics, a causal model (or structural causal model) is a conceptual model that describes the causal mechanisms of a system. Several types of causal notation may be used in the development of a causal model. Causal models can improve study ...

  4. Causality - Wikipedia

    en.wikipedia.org/wiki/Causality

    Causal efficacy cannot 'propagate' faster than light. Otherwise, reference coordinate systems could be constructed (using the Lorentz transform of special relativity) in which an observer would see an effect precede its cause (i.e. the postulate of causality would be violated). Causal notions appear in the context of the flow of mass-energy.

  5. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. [ 1 ] [ 2 ] The study of why things occur is called etiology , and can be described using the language of scientific causal notation .

  6. Rubin causal model - Wikipedia

    en.wikipedia.org/wiki/Rubin_causal_model

    Rubin defines a causal effect: Intuitively, the causal effect of one treatment, E, over another, C, for a particular unit and an interval of time from to is the difference between what would have happened at time if the unit had been exposed to E initiated at and what would have happened at if the unit had been exposed to C initiated at : 'If an hour ago I had taken two aspirins instead of ...

  7. Bayesian network - Wikipedia

    en.wikipedia.org/wiki/Bayesian_network

    A causal network is a Bayesian network with the requirement that the relationships be causal. The additional semantics of causal networks specify that if a node X is actively caused to be in a given state x (an action written as do( X = x )), then the probability density function changes to that of the network obtained by cutting the links from ...

  8. Why–because analysis - Wikipedia

    en.wikipedia.org/wiki/Why–because_analysis

    The result of a WBA is a why–because graph (WBG), a type of causal notation used to represent interdependencies within a system. The WBG depicts causal relations between factors of an accident. It is a directed acyclic graph where the nodes of the graph are factors.

  9. Causal reasoning - Wikipedia

    en.wikipedia.org/wiki/Causal_reasoning

    Causal reasoning is the process of identifying causality: the relationship between a cause and its effect.The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one.