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  2. Causal map - Wikipedia

    en.wikipedia.org/wiki/Causal_map

    In software testing, a causeeffect graph is a directed graph that maps a set of causes to a set of effects. The causes may be thought of as the input to the program, and the effects may be thought of as the output. Usually the graph shows the nodes representing the causes on the left side and the nodes representing the effects on the right side.

  3. 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.

  4. 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.

  5. Causal reasoning - Wikipedia

    en.wikipedia.org/wiki/Causal_reasoning

    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.

  6. The Book of Why - Wikipedia

    en.wikipedia.org/wiki/The_Book_of_Why

    9780141982410. Preceded by. Causal Inference in Statistics: A Primer. The Book of Why: The New Science of Cause and Effect is a 2018 nonfiction book by computer scientist Judea Pearl and writer Dana Mackenzie. The book explores the subject of causality and causal inference from statistical and philosophical points of view for a general audience.

  7. 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 ...

  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. Causality - Wikipedia

    en.wikipedia.org/wiki/Causality

    Causality is an influence by which one event, process, state, or object (acause) 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, [ 1 ...