Outliers are basically numbers, in a set of numbers, that don't belong in that set and/or that stand out. For example, in the data set {3, 5, 4, 4, 6, 2, 25, 5, 6, 2} the value of 25 is an outlier.
For a set of numerical data (a set of numbers), any value (number) that is markedly smaller or larger than other values is an outlier. This is the qualitative definition.
Mathematically, a quantitative definition often given is that an outliers is any number that is more than 1.5 times the interquartile range away from the median. However, this is not definitive and in some cases other definitions will be used.
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The one that does not belong
0s are not the outlier values
The answer depends on the nature of the outlier. Removing a very small outlier will increase the mean while removing a large outlier will reduce the mean.
there is no outlier because there isn't a data set to go along with it. so theres no outlier
the most common cause of an outlier is an error in the recording of data.