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  2. 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 ...

  3. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    For example, oxygen is necessary for fire. But one cannot assume that everywhere there is oxygen, there is fire. A condition X is sufficient for Y if X, by itself, is enough to bring about Y. For example, riding the bus is a sufficient mode of transportation to get to work.

  4. Forking paths problem - Wikipedia

    en.wikipedia.org/wiki/Forking_paths_problem

    A multiverse analysis is an approach that acknowledges the multitude of analytical paths available when analyzing data. The concept is inspired by the metaphorical "garden of forking paths," which represents the multitude of potential analyses that could be conducted on a single dataset.

  5. 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 ...

  6. Correlation does not imply causation - Wikipedia

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

    [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

  7. Data dredging - Wikipedia

    en.wikipedia.org/wiki/Data_dredging

    Lastly, a statistical significance test is carried out to see how likely the results are by chance alone (also called testing against the null hypothesis). A key point in proper statistical analysis is to test a hypothesis with evidence (data) that was not used in constructing the hypothesis.

  8. Base rate fallacy - Wikipedia

    en.wikipedia.org/wiki/Base_rate_fallacy

    An example of the base rate fallacy is the false positive paradox (also known as accuracy paradox).This paradox describes situations where there are more false positive test results than true positives (this means the classifier has a low precision).

  9. Cherry picking - Wikipedia

    en.wikipedia.org/wiki/Cherry_picking

    Cherry picking, suppressing evidence, or the fallacy of incomplete evidence is the act of pointing to individual cases or data that seem to confirm a particular position while ignoring a significant portion of related and similar cases or data that may contradict that position. Cherry picking may be committed intentionally or unintentionally.