> ## Documentation Index > Fetch the complete documentation index at: https://docs.elementary-data.com/llms.txt > Use this file to discover all available pages before exploring further. # Data anomaly detection method Elementary uses "[standard score](https://en.wikipedia.org/wiki/Standard_score)", also known as "Z-score" for anomaly detection. This score represents the number of standard deviations of a value from the average of a set of values. According to the [empirical rule](https://www.statisticshowto.com/probability-and-statistics/statistics-definitions/empirical-rule-2/), in a standard normal distribution: * **\~68%** of values have an absolute **z-score of 1 or less.** * **\~95%** of values have an absolute **z-score of 2 or less.** * **\~99.7%** of values have an absolute **z-score of 3 or less.** Values with a **standard score of 3 and above are [considered outliers](https://www.ctspedia.org/do/view/CTSpedia/OutLier)**, and this is a recommended threshold for anomaly detection. This is the default Elementary uses as well, and it can be changed using the var `anomaly_score_threshold` in the [global configuration](/data-tests/elementary-tests-configuration). You can use the model `anomaly_sensitivity` to see if values of metrics from your last run would have been considered anomalies in different scores. **This can help you decide if there is a need to adjust the sensitivity:** Z Score