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  2. Correlation does not imply causation - Wikipedia

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

    The above example commits the correlation-implies-causation fallacy, as it prematurely concludes that sleeping with one's shoes on causes headache. A more plausible explanation is that both are caused by a third factor, in this case going to bed drunk, which thereby gives rise to a correlation. So the conclusion is false. Example 2

  3. Questionable cause - Wikipedia

    en.wikipedia.org/wiki/Questionable_cause

    Therefore the sunny day causes me to score well on the test." Here is the example the two events may coincide or correlate, but have no causal connection. [2] Fallacies of questionable cause include: Circular cause and consequence [citation needed] Correlation implies causation (cum hoc, ergo propter hoc) Third-cause fallacy; Wrong direction

  4. Correlative-based fallacies - Wikipedia

    en.wikipedia.org/wiki/Correlative-based_fallacies

    Fallacies based on correlatives include: [1] False dilemma or false correlative. Here something which is not a correlative is treated as a correlative, excluding some other possibility.

  5. 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]

  6. 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 ...

  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. G20 leaders can stop climate breakdown, but rules must ... - AOL

    www.aol.com/news/g20-leaders-stop-climate...

    NEW DELHI (Reuters) -U.N. Secretary-General Antonio Guterres said G20 leaders have the power to reset a climate crisis that is "spinning out of control" and urged them to reshape global financial ...

  9. Magical thinking - Wikipedia

    en.wikipedia.org/wiki/Magical_thinking

    [1] [2] [3] Examples include the idea that personal thoughts can influence the external world without acting on them, or that objects must be causally connected if they resemble each other or have come into contact with each other in the past. [1] [2] [4] Magical thinking is a type of fallacious thinking and is a common source of invalid causal ...