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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]
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.
Simpson's paradox has been used to illustrate the kind of misleading results that the misuse of statistics can generate. [7] [8] Edward H. Simpson first described this phenomenon in a technical paper in 1951, [9] but the statisticians Karl Pearson (in 1899 [10]) and Udny Yule (in 1903 [11]) had mentioned similar effects earlier.
The president tweeted misleading statistics about voter fraud on Sunday, claiming that nearly 60,000 non-citizens voted in Texas. Trump cites misleading stats in alleging Texas voter fraud Skip to ...
George Box. The phrase "all models are wrong" was first attributed to George Box in a 1976 paper published in the Journal of the American Statistical Association.In the paper, Box uses the phrase to refer to the limitations of models, arguing that while no model is ever completely accurate, simpler models can still provide valuable insights if applied judiciously. [1]
Pages in category "Misuse of statistics" The following 27 pages are in this category, out of 27 total. ... Misleading graph; Moving the goalposts; P. P-hacking;
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Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the syndemic involving obesity and diabetes may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.