Outlier Tests

Tests on outliers in data sets can be used to

• check if methods of measurement are reliable
• check the reliability of data sets

Several outlier tests are available, each of them having its own special advantages and drawbacks. Following is a short description of the most commonly used strategies to identify outliers:

• Basic rules using the standard deviation and the interquartile range
• Dean-Dixon Test
• Outlier test according to Walsh
• Grubbs test for outliers
• Significance of extreme values
• Nalimov test

Nonetheless there is one common rule which should be strictly obeyed: do not eliminate outliers successively. To be specific, do not identify an outlier, eliminate it and recalculate the statistics to perform another outlier detection and elimination. All outliers must be removed in one single calculation.