Outlier: Difference between revisions

From Citizendium
Jump to navigation Jump to search
imported>Alex Wiegand
No edit summary
imported>Bruce M. Tindall
(de-orphanize & copyedit)
 
(One intermediate revision by the same user not shown)
Line 1: Line 1:
An '''outlier''' is an observation in a data set that is so different from the other observations that it appears not to belong in the data set.
{{subpages}}
In [[statistics theory|statistics]], an '''outlier''' is an observation in a data set that is so different from the other observations that it appears not to belong in the data set.


The most common use of outliers is to exclude them from statistical calculations.
The most common treatment of outliers is to exclude them from statistical calculations.


The reasoning behind this is that the outliers must have been generated by a different phenomenon to the rest of the observations, for example an error in measurement, and would therefore make statistical analysis less accurate.
The reasoning behind this is that the outliers must have been generated by a different phenomenon from the rest of the observations, for example an error in measurement, and would therefore make statistical analysis less accurate.


==References==
==References==
<references/>
<references/>
[[Category:CZ Live]]
[[Category:Stub Articles]]
[[Category:Computers Workgroup]]

Latest revision as of 15:01, 25 November 2010

This article is a stub and thus not approved.
Main Article
Discussion
Related Articles  [?]
Bibliography  [?]
External Links  [?]
Citable Version  [?]
 
This editable Main Article is under development and subject to a disclaimer.

In statistics, an outlier is an observation in a data set that is so different from the other observations that it appears not to belong in the data set.

The most common treatment of outliers is to exclude them from statistical calculations.

The reasoning behind this is that the outliers must have been generated by a different phenomenon from the rest of the observations, for example an error in measurement, and would therefore make statistical analysis less accurate.

References