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Outliers Alert
Indicates the presence of uncommonly large or small numbers, potentially from data entry errors or rare events. Outliers influence averages, which can affect the accuracy of insights, predictions, and improvements.
Note Einstein Discovery stories are now models. We wish we could snap our fingers to update
the name everywhere, but you can expect to see the previous name in a few places until we
replace it.
Actions to Consider
There are two types of outliers:
- incorrect values due to data entry errors, process errors, or other problems
- correct values that reflect an extraordinary, non-recurring event, or infrequent event
Investigate deeper to determine which outliers to keep and which to omit from your model. Exclude incorrect values from your model and consider fixing them at the source.
Detection Methodology
For a variable, Einstein Discovery:
- calculates the global mean and global standard deviation of its values
- designates an outlier as any value that is greater than, or less than, five standard deviations away from the global mean
The alert indicates that at least one outlier was detected.
See Also
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