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A descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features from a collection of information, [1] while descriptive statistics (in the mass noun sense) is the process of using and analysing those statistics. Descriptive statistics is distinguished from inferential statistics (or ...
Some statistics are simply irrelevant to an issue. [38] Certain advertising phrasing such as "[m]ore than 99 in 100," may be misinterpreted as 100%. [39] Anscombe's quartet is a made-up dataset that exemplifies the shortcomings of simple descriptive statistics (and the value of data plotting before numerical analysis).
It has been proposed that just as memes are analogous to genes, memetics is analogous to genetics. Memetics has been deemed a pseudoscience on several fronts. [447] Its proponents' assertions have been labeled "untested, unsupported or incorrect". [447] Supporters of memetics include EO Wilson, Douglas Hofstadter and many others.
The Datasaurus dozen comprises thirteen data sets that have nearly identical simple descriptive statistics to two decimal places, yet have very different distributions and appear very different when graphed. [1] It was inspired by the smaller Anscombe's quartet that was created in 1973.
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]
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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]