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  2. Causal reasoning - Wikipedia

    en.wikipedia.org/wiki/Causal_reasoning

    In common-effect relationships, several causes converge in one effect: Example of multiple causes with a single effect An increase in government spending is an example of one effect with several causes (reduced unemployment, decreased currency value, and increased deficit). In causal chains one cause triggers an effect, which triggers another ...

  3. Causality - Wikipedia

    en.wikipedia.org/wiki/Causality

    Causality. 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 at least partly responsible for the effect, and the effect is at least partly dependent on the cause. In general, a process can have multiple causes ...

  4. Correlation does not imply causation - Wikipedia

    en.wikipedia.org/wiki/Correlation_does_not_imply...

    The phrase " correlation does not imply causation " refers to the inability to legitimately deduce a cause-and-effect relationship between two events or variables solely on the basis of an observed association or correlation between them. [1][2] The idea that "correlation implies causation" is an example of a questionable-cause logical fallacy ...

  5. Bradford Hill criteria - Wikipedia

    en.wikipedia.org/wiki/Bradford_Hill_criteria

    Bradford Hill criteria. The Bradford Hill criteria, otherwise known as Hill's criteria for causation, are a group of nine principles that can be useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an observed effect and have been widely used in public health research.

  6. Ishikawa diagram - Wikipedia

    en.wikipedia.org/wiki/Ishikawa_diagram

    Sample Ishikawa diagram shows the causes contributing to problem. The defect, or the problem to be solved, [1] is shown as the fish's head, facing to the right, with the causes extending to the left as fishbones; the ribs branch off the backbone for major causes, with sub-branches for root-causes, to as many levels as required.

  7. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. 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 ...

  8. Universal causation - Wikipedia

    en.wikipedia.org/wiki/Universal_causation

    Universal causation. Universal causation is the proposition that everything in the universe has a cause and is thus an effect of that cause. This means that if a given event occurs, then this is the result of a previous, related event. [1] If an object is in a certain state, then it is in that state as a result of another object interacting ...

  9. Proximate and ultimate causation - Wikipedia

    en.wikipedia.org/wiki/Proximate_and_ultimate...

    Causes and effects. Causes and effects from a common cause. One famous example of the importance of this is the Duhem–Quine thesis, which demonstrates that it is impossible to test a hypothesis in isolation, because an empirical test of the hypothesis requires one or more background assumptions. One way to solve this issue is to employ ...