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  2. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    McNamara fallacy (quantitative fallacy) – making an argument using only quantitative observations (measurements, statistical or numerical values) and discounting subjective information that focuses on quality (traits, features, or relationships).

  3. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    In others, it is purposeful and for the gain of the perpetrator. 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. Misuses can be easy to ...

  4. Statistical syllogism - Wikipedia

    en.wikipedia.org/wiki/Statistical_syllogism

    In the above example, if 99% of people are taller than 26 inches, then the probability of the conclusion being true is 99%. Two dicto simpliciter fallacies can occur in statistical syllogisms. They are "accident" and "converse accident". Faulty generalization fallacies can also

  5. Lies, damned lies, and statistics - Wikipedia

    en.wikipedia.org/wiki/Lies,_damned_lies,_and...

    The origin of the phrase "Lies, damned lies, and statistics" is unclear, but Mark Twain attributed it to Benjamin Disraeli [1] "Lies, damned lies, and statistics" is a phrase describing the persuasive power of statistics to bolster weak arguments, "one of the best, and best-known" critiques of applied statistics. [2]

  6. Faulty generalization - Wikipedia

    en.wikipedia.org/wiki/Faulty_generalization

    In statistics, it may involve basing broad conclusions regarding a statistical survey from a small sample group that fails to sufficiently represent an entire population. [1] [6] [7] Its opposite fallacy is called slothful induction, which consists of denying a reasonable conclusion of an inductive argument (e.g. "it was just a coincidence").

  7. Forking paths problem - Wikipedia

    en.wikipedia.org/wiki/Forking_paths_problem

    Exploring a forking decision-tree while analyzing data was at one point grouped with the multiple comparisons problem as an example of poor statistical method. However Gelman and Loken demonstrated [2] that this can happen implicitly by researchers aware of best practices who only make a single comparison and only evaluate their data once.

  8. Texas sharpshooter fallacy - Wikipedia

    en.wikipedia.org/wiki/Texas_sharpshooter_fallacy

    The Texas sharpshooter fallacy is an informal fallacy which is committed when differences in data are ignored, but similarities are overemphasized. From this reasoning, a false conclusion is inferred. [1] This fallacy is the philosophical or rhetorical application of the multiple comparisons problem (in statistics) and apophenia (in cognitive ...

  9. List of cognitive biases - Wikipedia

    en.wikipedia.org/wiki/List_of_cognitive_biases

    G. I. Joe fallacy, the tendency to think that knowing about cognitive bias is enough to overcome it. [65] Gambler's fallacy, the tendency to think that future probabilities are altered by past events, when in reality they are unchanged. The fallacy arises from an erroneous conceptualization of the law of large numbers. For example, "I've ...