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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.
Data dredging (also known as data snooping or p-hacking) [1] [a] is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives.
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.
Pages in category "Misuse of statistics" The following 27 pages are in this category, out of 27 total. This list may not reflect recent changes. ...
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.
Misuse of p-values is common in scientific research and scientific education. p -values are often used or interpreted incorrectly; [ 1 ] the American Statistical Association states that p -values can indicate how incompatible the data are with a specified statistical model. [ 2 ]
Over the past quarter century, Slattery’s for-profit prison enterprises have run afoul of the Justice Department and authorities in New York, Florida, Maryland, Nevada and Texas for alleged offenses ranging from condoning abuse of inmates to plying politicians with undisclosed gifts while seeking to secure state contracts.
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]