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  2. 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.

  3. Correlation does not imply causation - Wikipedia

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

    Example 3. In other cases it may simply be unclear which is the cause and which is the effect. For example: Children that watch a lot of TV are the most violent. Clearly, TV makes children more violent. This could easily be the other way round; that is, violent children like watching more TV than less violent ones. Example 4

  4. Causality - Wikipedia

    en.wikipedia.org/wiki/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. [1]

  5. Universal causation - Wikipedia

    en.wikipedia.org/wiki/Universal_causation

    Nothing takes place without a cause. The magnitude of an effect is proportional to the magnitude of its cause. To every action there is an equal and opposed reaction. Whewell writes that the first axiom is so clear that it requires no proof if only the idea of cause is understood. [7]

  6. Bradford Hill criteria - Wikipedia

    en.wikipedia.org/wiki/Bradford_Hill_criteria

    Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). Biological gradient (dose–response relationship): Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of ...

  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.

  8. Causal analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_analysis

    Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...

  9. Mill's methods - Wikipedia

    en.wikipedia.org/wiki/Mill's_Methods

    Therefore A is the cause, or the effect, or a part of the cause of w. As an example of the method of difference, consider two similar countries. Country A has a centre-right government, a unitary system and was a former colony. Country B has a centre-right government, a unitary system but was never a colony.