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  2. Correlation does not imply causation - Wikipedia

    en.wikipedia.org/wiki/Correlation_does_not_imply...

    [3] That is the meaning intended by statisticians when they say causation is not certain. Indeed, p implies q has the technical meaning of the material conditional: if p then q symbolized as p → q. That is, "if circumstance p is true, then q follows." In that sense, it is always correct to say "Correlation does not imply causation."

  3. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    [1] [2] [3] The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system. Confounders are threats to internal validity. [4]

  4. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    Graphical model: Whereas a mediator is a factor in the causal chain (top), a confounder is a spurious factor incorrectly implying causation (bottom). In statistics, a spurious relationship or spurious correlation [1] [2] is a mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third ...

  5. How to Lie with Statistics - Wikipedia

    en.wikipedia.org/wiki/How_to_Lie_with_Statistics

    Themes of the book include "Correlation does not imply causation" and "Using random sampling." It also shows how statistical graphs can be used to distort reality. For example, by truncating the bottom of a line or bar chart so that differences seem larger than they are.

  6. Good to Great - Wikipedia

    en.wikipedia.org/wiki/Good_to_Great

    He also notes the Wrong End of the Stick delusion used in the hedgehog claims of the book in that successful companies have a luxury of focus which is not possible for less successful companies. Finally, he notes the presence of the Organizational Physics delusion in that Collins does not carefully avoid confusing correlation with causation. [11]

  7. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    When a statistical test shows a correlation between A and B, there are usually six possibilities: A causes B. B causes A. A and B both partly cause each other. A and B are both caused by a third factor, C. B is caused by C which is correlated to A. The observed correlation was due purely to chance.

  8. 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 ...

  9. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    Cum hoc ergo propter hoc (Latin for 'with this, therefore because of this'; correlation implies causation; faulty cause/effect, coincidental correlation, correlation without causation) – a faulty assumption that, because there is a correlation between two variables, one caused the other. [57]