How outliers are calculated

Outliers are data points that differ significantly from the rest of the data and may represent errors, anomalies, or important insights.

Our method for detecting outliers is based on the standard deviation, which measures how much the data deviates from the mean. If a data point is several standard deviations away from the mean, it is considered an outlier.

The number of standard deviations required to flag a data point as an outlier is up to you and can be set via our outlier slider:

After you set the sensitivity level for outlier detection, a lower and upper bound is calculated.

Lower boundary: μ - u*σ

Upper boundary: μ + u*σ

μ = mean of the column

u = user input between 1 and 5 via the outlier slider

σ = Standard deviation of the column

If a cell value is outside the boundaries, then it is flagged as an outlier.