Contents
- Index
Outlier
A true outlier is a point that is not from the same distribution as the other values, but instead something happened to it (typically an error) to make it different than the other values. For example, consider a filling operation where bags are filled with a solution. Bags are consistently in the 50 to 55 mL range. However, occasionally a half filled bag is found (15-35 mL). An investigation into the cause identified these bags were being removed from the filling nozzle before the cycle was completed. As a result, some the solution missed going into the bag. An outlier can be the result of either a manufacturing error or a measurement error.
It can be difficult to distinguish between an outlier relative to the normal distribution or an extreme value out in the tail of a long tailed distribution. For a data point to be considered an outlier relative to the normal distribution, it must generally be at least 4.5 standard deviations from the average. In Tab 7: Outliers of the Test Distribution window values are flagged as definite outliers if they are 10 or more standard deviations from the average. Between 4.5 and 10 standard deviations they are flagged as either outliers from the normal distributions or extreme values from a long tailed distribution