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The bald want a cure that is both statistically and practically significant; It will probably work and if it does, it will have a big hairy effect. Scientific publication often requires only statistical significance. This has led to complaints (for the last 50 years) that statistical significance testing is a misuse of statistics. [25]
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. ...
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.
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.
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.
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]
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For example, the employment data graph to the right, taken from the New Deal article in June 2008, purports to illustrate the level of employment in the United States of America over the years. The amount of employment visually appears to triple from 1933 to 1941.