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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 map - Wikipedia

    en.wikipedia.org/wiki/Causal_map

    In software testing, a cause–effect 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.

  4. Causal loop diagram - Wikipedia

    en.wikipedia.org/wiki/Causal_loop_diagram

    The use of words and arrows (known in network theory as nodes and edges) to construct directed graph models of cause and effect dates back, at least, to the use of path analysis by Sewall Wright in 1918.

  5. Causal graph - Wikipedia

    en.wikipedia.org/wiki/Causal_graph

    Figure 1 is a causal graph that represents this model specification. Each variable in the model has a corresponding node or vertex in the graph. Additionally, for each equation, arrows are drawn from the independent variables to the dependent variables. These arrows reflect the direction of causation.

  6. Causal notation - Wikipedia

    en.wikipedia.org/wiki/Causal_notation

    A causal diagram consists of a set of nodes which may or may not be interlinked by arrows. Arrows between nodes denote causal relationships with the arrow pointing from the cause to the effect. There exist several forms of causal diagrams including Ishikawa diagrams, directed acyclic graphs, causal loop diagrams, [10] and why-because graphs (WBGs

  7. Root cause analysis - Wikipedia

    en.wikipedia.org/wiki/Root_cause_analysis

    In science and engineering, root cause analysis (RCA) is a method of problem solving used for identifying the root causes of faults or problems. [1] It is widely used in IT operations, manufacturing, telecommunications, industrial process control, accident analysis (e.g., in aviation, [2] rail transport, or nuclear plants), medical diagnosis, the healthcare industry (e.g., for epidemiology ...

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