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The misuse of Statistics can trick the observer who does not understand them into believing something other than what the data shows or what is really 'true'. That is, a misuse of statistics occurs when an argument uses statistics to assert a falsehood. In some cases, the misuse may be accidental.
Michael LaCour (US), former graduate student in political science at UCLA, was the lead author of the 2014 article "When contact changes minds". Published in Science and making international headlines, the paper was later retracted because of numerous irregularities in the methodology and falsified data.
Neo-colonial research or neo-colonial science, [36] [37] frequently described as helicopter research, [36] parachute science [38] [39] or research, [40] parasitic research, [41] [42] or safari study, [43] is when researchers from wealthier countries go to a developing country, collect information, travel back to their country, analyze the data ...
How to Read Numbers: A Guide to Statistics in the News (and Knowing When to Trust Them) is a 2021 British book by Tom and David Chivers. It describes misleading uses of statistics in the news, with contemporary examples about the COVID-19 pandemic, healthcare, politics and crime. The book was conceived by the authors, who are cousins, in early ...
Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, [ 1 ] [ 2 ] [ 3 ] and is particularly problematic when frequency data are unduly given ...
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]
Leek summarized the key points of agreement as: when talking about the science-wise false discovery rate one has to bring data; there are different frameworks for estimating the science-wise false discovery rate; and "it is pretty unlikely that most published research is false", but that probably varies by one's definition of "most" and "false".
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