# Tell me how isoutlier function works

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Lev Mihailov on 2 Sep 2019
Edited: Adam Danz on 22 Nov 2019
There is such a wonderful function isoutlier, but i can't understand
data=[27 27 17 64 27 27] % gives me the correct values
TF = isoutlier(data);
however, when the number of my values ​​increases significantly, I get errors
shows me the value 17, but does not show 64

Steven Lord on 22 Nov 2019
Can you share a small section of code that when you run you "get errors" along with the full text of those error messages (all the text displayed in red) and any warning messages you may have received (all the text displayed in orange?)
Adam Danz on 22 Nov 2019
I'm guessing that "errors" means unexpected results such as points that aren't labeled as an outlier that the OP expects to be an outlier or vice versa.

Adam Danz on 2 Sep 2019
Edited: Adam Danz on 22 Nov 2019
The algorithm is explained in the documentation. "By default, an outlier is a value that is more than three scaled median absolute deviations (MAD) away from the median". The link provides a relatively simple equation showing how the MAD are calculated.
The reason the outlier at y=64 is not identified when the number of values increase is because your median changes and 64 is no longer 3xMAD.
There are other methods you could try. Outlier detection is not trivial and there's no sure-fire way that detects all outliers in all situations. Even the definition of what constitutes an outlier is subjective in many cases.
If all of your outliers are large, positive spikes like in your example, you could simply set a threshold that is n standard deviations from the mean and any data points beyond that value can be considered outliers.