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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. 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.

  4. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    Hasty generalization (fallacy of insufficient statistics, fallacy of insufficient sample, fallacy of the lonely fact, hasty induction, secundum quid, converse accident, jumping to conclusions) – basing a broad conclusion on a small or unrepresentative sample. [55]

  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. 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.

  7. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a "discovery". A stated confidence level generally applies only to each test considered individually, but often it is desirable to have a confidence level for the whole family of simultaneous tests. [4]

  8. 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.

  9. Why Most Published Research Findings Are False - Wikipedia

    en.wikipedia.org/wiki/Why_Most_Published...

    Statistical significance is formalized in terms of probability, with its p-value measure being reported in the scientific literature as a screening mechanism. Ioannidis posited assumptions about the way people perform and report these tests; then he constructed a statistical model which indicates that most published findings are likely false ...