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  2. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator.

  3. How to Lie with Statistics - Wikipedia

    en.wikipedia.org/wiki/How_to_Lie_with_Statistics

    The book is a brief, breezy illustrated volume outlining the misuse of statistics and errors in the interpretation of statistics, and how errors create incorrect conclusions. In the 1960s and 1970s, it became a standard textbook introduction to the subject of statistics for many college students.

  4. Misleading graph - Wikipedia

    en.wikipedia.org/wiki/Misleading_graph

    In statistics, a misleading graph, also known as a distorted graph, is a graph that misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it. Graphs may be misleading by being excessively complex or poorly constructed.

  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. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...

  7. American teens are increasingly misled by fake content ... - AOL

    www.aol.com/american-teens-increasingly-misled...

    As AI has made fake content much easier to produce, a growing number of American teenagers say they are being misled by AI-generated photos, videos or other content on the internet, a new study shows.

  8. Data dredging - Wikipedia

    en.wikipedia.org/wiki/Data_dredging

    If they are not cautious, researchers using data mining techniques can be easily misled by these results. The term p-hacking (in reference to p-values) was coined in a 2014 paper by the three researchers behind the blog Data Colada, which has been focusing on uncovering such problems in social sciences research. [3] [4] [5]

  9. Are You Being Misled In This Election? - AOL

    www.aol.com/news/2012-11-02-potential-disaster...

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