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Wednesday, May 3, 2017

The effect of outliers on statistical properties - Anscombe's quartet

Anscombe's quartet comprises four datasets that have nearly identical simple descriptive statistics, yet appear very different when graphed. Each dataset consists of eleven (x,y) points. They were constructed in 1973 by the statistician Francis Anscombe to demonstrate both the importance of graphing data before analyzing it and the effect of outliers on statistical properties. He described the article as being intended to attack the impression among statisticians that "numerical calculations are exact, but graphs are rough."[1]

Source: https://en.wikipedia.org/wiki/Anscombe%27s_quartet


(You can easily check this in R by loading the data with data(anscombe).) But what you might not realize is that it's possible to generate bivariate data with a given mean, median, and correlation in any shape you like — even a dinosaur:


Source: The Datasaurus Dozen
Posted: 02 May 2017 08:16 AM PDT
(This article was first published on Revolutions, and kindly contributed to R-bloggers)