Outlier
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Definition
Outlier

Tip: Identifying outliers...
There is no universallyagreedon criterion for defining an outlier, however using [math]1.5\, [/math] times the interquartile range (IQR) to identify data values substantially below the first quartile (Q1) or above the third quartile (Q3) provides a good rule of thumb. With this rule an observation is considered a suspected outlier if it is:
 below [math]\ Q1  1.5(IQR)\, [/math]
 above [math]\ Q3 + 1.5(IQR)\, [/math]
Regardless of your method for identifying outliers, always assess the effects of outliers on the statistical conclusions.
Examples
The histogram shown below displays a dataset with one high outlier  a value between 75 and 80, with the next highest value between 50 and 55.
Web Resources

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