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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. Causal loop diagram - Wikipedia

    en.wikipedia.org/wiki/Causal_loop_diagram

    Example of a positive reinforcing loop between two values: bank balance and earned interest. A causal loop diagram (CLD) is a causal diagram that visualizes how different variables in a system are causally interrelated. The diagram consists of a set of words and arrows.

  4. GHS hazard pictograms - Wikipedia

    en.wikipedia.org/wiki/GHS_hazard_pictograms

    a signal word – either Danger or Warning – where necessary; hazard statements, indicating the nature and degree of the risks posed by the product; precautionary statements, indicating how the product should be handled to minimize risks to the user (as well as to other people and the general environment)

  5. Ishikawa diagram - Wikipedia

    en.wikipedia.org/wiki/Ishikawa_diagram

    Common uses of the Ishikawa diagram are product design and quality defect prevention to identify potential factors causing an overall effect. Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify and classify these sources of variation.

  6. List of effects - Wikipedia

    en.wikipedia.org/wiki/List_of_effects

    CNN effect (civil–military relations) (CNN) (news media) (warfare of the modern era) Coandă effect (aerodynamics) (boundary layers) (physical phenomena) Coattail effect (political terms) Cobra effect (Economics) Cocktail party effect (acoustical signal processing) (attention) Cohort effect; Common-ion effect (ions) (physical chemistry)

  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. The Mandela effect: 10 examples that explain what it is and ...

    www.aol.com/lifestyle/mandela-effect-10-examples...

    Popular examples of the Mandela effect. Here are some Mandela effect examples that have confused me over the years — and many others too. Grab your friends and see which false memories you may ...

  9. 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 ...