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  2. 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.

  3. 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 ...

  4. 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.

  5. Causal research - Wikipedia

    en.wikipedia.org/wiki/Causal_research

    Causal research, is the investigation of (research into) cause-relationships. [ 1 ] [ 2 ] [ 3 ] To determine causality, variation in the variable presumed to influence the difference in another variable(s) must be detected, and then the variations from the other variable(s) must be calculated (s).

  6. Accident analysis - Wikipedia

    en.wikipedia.org/wiki/Accident_Analysis

    Ishikawa Diagram: Takes into account environmental, human, methodical, and equipment causes that can lead to a problem. Using this model, an accident analyst could work backwards from the problem to find and mitigate potential causes. Fault Tree Analysis: Uses a tree type "yes/no" cause and effect analysis to determine potential causes 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 model - Wikipedia

    en.wikipedia.org/wiki/Causal_model

    Judea Pearl defines a causal model as an ordered triple ,, , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U ...

  9. Causal loop diagram - Wikipedia

    en.wikipedia.org/wiki/Causal_loop_diagram

    A link marked -indicates a negative relation where an increase in the causal variable leads, all else equal, to a decrease in the effect variable, or a decrease in the causal variable leads, all else equal, to an increase in the effect variable. A positive causal link can be said to lead to a change in the same direction, and an opposite link ...