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  2. Causal notation - Wikipedia

    en.wikipedia.org/wiki/Causal_notation

    In nature and human societies, many phenomena have causal relationships where one phenomenon A (a cause) impacts another phenomenon B (an effect). Establishing causal relationships is the aim of many scientific studies across fields ranging from biology [ 1 ] and physics [ 2 ] to social sciences and economics . [ 3 ]

  3. Causality - Wikipedia

    en.wikipedia.org/wiki/Causality

    In Part III, section XV of his book A Treatise of Human Nature, Hume expanded this to a list of eight ways of judging whether two things might be cause and effect. The first three: "The cause and effect must be contiguous in space and time." "The cause must be prior to the effect." "There must be a constant union betwixt the cause and effect.

  4. Five whys - Wikipedia

    en.wikipedia.org/wiki/Five_whys

    Five whys (or 5 whys) is an iterative interrogative technique used to explore the cause-and-effect relationships underlying a particular problem. [1] The primary goal of the technique is to determine the root cause of a defect or problem by repeating the question "why?" five times, each time directing the current "why" to the answer of the ...

  5. Four causes - Wikipedia

    en.wikipedia.org/wiki/Four_causes

    Furthermore, the second principle also establishes a qualitative link: the cause can only transmit its own essence to the effect. For example, a dog cannot transmit the essence of a feline to its young, but only that of a dog. [45]

  6. Rhetorical modes - Wikipedia

    en.wikipedia.org/wiki/Rhetorical_modes

    Examples are the satiric mode, the ironic, the comic, the pastoral, and the didactic. [ 2 ] Frederick Crews uses the term to mean a type of essay and categorizes essays as falling into four types, corresponding to four basic functions of prose: narration , or telling; description , or picturing; exposition , or explaining; and argument , or ...

  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.

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