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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. Fact-checking - Wikipedia

    en.wikipedia.org/wiki/Fact-checking

    Recently, a lot of work has gone into helping detect and identify fake news through machine learning and artificial intelligence. [76] [77] [78] In 2018, researchers at MIT's CSAIL created and tested a machine learning algorithm to identify false information by looking for common patterns, words, and symbols that typically appear in fake news. [79]

  4. Misinformation - Wikipedia

    en.wikipedia.org/wiki/Misinformation

    Misinformation can also often be observed as news events are unfolding and questionable or unverified information fills information gaps. Even if later retracted, false information can continue to influence actions and memory. [26] Rumors are unverified information not attributed to any particular source and may be either true or false. [27]

  5. Bias (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bias_(statistics)

    In educational measurement, bias is defined as "Systematic errors in test content, test administration, and/or scoring procedures that can cause some test takers to get either lower or higher scores than their true ability would merit." [16] The source of the bias is irrelevant to the trait the test is intended to measure.

  6. List of fallacies - Wikipedia

    en.wikipedia.org/wiki/List_of_fallacies

    Persuasive definition – purporting to use the "true" or "commonly accepted" meaning of a term while, in reality, using an uncommon or altered definition. (cf. the if-by-whiskey fallacy) Ecological fallacy – inferring about the nature of an entity based solely upon aggregate statistics collected for the group to which that entity belongs. [27]

  7. Data dredging - Wikipedia

    en.wikipedia.org/wiki/Data_dredging

    In fact, if the null hypothesis is true, then any significance level can be reached if one is allowed to keep collecting data and stop when the desired p-value (calculated as if one has always been planning to collect exactly this much data) is obtained. [7] For a concrete example of testing for a fair coin, see p-value § Optional stopping.

  8. 105 True or False Questions—Fun Facts To Keep You ... - AOL

    www.aol.com/lifestyle/105-true-false-questions...

    True or False Questions About Disney. 86. Cars was Pixar’s first movie. Answer: False – it was Toy Story. 87. Disney’s first full-color animated film was Snow White and the Seven Dwarfs.

  9. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.

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