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[1] [2] The idea that "correlation implies causation" is an example of a questionable-cause logical fallacy, in which two events occurring together are taken to have established a cause-and-effect relationship. This fallacy is also known by the Latin phrase cum hoc ergo propter hoc ('with this, therefore because of
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 ...
The fallacy of accident (also called destroying the exception or a dicto simpliciter ad dictum secundum quid) is an informal fallacy where a general rule is applied to an exceptional case. The fallacy of accident gets its name from the fact that one or more accidental features of the specific case make it an exception to the rule.
Naturalistic fallacy fallacy is a type of argument from fallacy. Straw man fallacy – refuting an argument different from the one actually under discussion, while not recognizing or acknowledging the distinction. [110] Texas sharpshooter fallacy – improperly asserting a cause to explain a cluster of data. [111]
The questionable cause—also known as causal fallacy, false cause, or non causa pro causa ("non-cause for cause" in Latin)—is a category of informal fallacies in which the cause or causes is/are incorrectly identified. In other words, it is a fallacy of reaching a conclusion that one thing caused another, simply because they are regularly ...
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.
An affidavit previously obtained by the local news stations stated that Jacob left his girlfriend's house, saying he was going to have dinner with his family.
When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy. The consequences of such misinterpretations can be quite severe. For example, in medical science, correcting a falsehood may take decades and cost lives.