The terms are largely used in an interchangeable way.

"Outlier" refers to something lying outside the norm - so it is "anomalous".

But I have the inpression that "outlier" is usually used for very rare observations. In statistics, on a normal distribution, you would consider three sigma to be outliers. That is 99.7% of your objects are expected to be "normal".

"Anomaly" is used much more liberally. If you suddenly have millions of visitors on your website, these are not rare visitors. The sudden increase in visitors however is still "anomalous", whereas each individual visitor is not an "outlier".

The terms are largely used in an interchangeable way. "Outlier" refers to something lying outside the norm - so it is "anomalous". But I have the inpression that "outlier" is usually used for very rare observations. In statistics, on a normal distribution, you would consider three sigma to be outliers. That is 99.7% of your objects are expected to be "normal". "Anomaly" is used much more liberally. If you suddenly have millions of visitors on your website, these are not rare visitors. The sudden increase in visitors however is still "anomalous", whereas each individual visitor is not an "outlier".

It may have been in this article where I saw these differences discussed, but I can't access it right now, unfortunately.

Statistical Analysis and Data Mining, Volume 5, Issue 5, October 2012, Pages 363–387 A survey on unsupervised outlier detection in high-dimensional numerical data