Removing outliers is legitimate only for specific reasons. Outliers can be very informative about the subject-area and data collection process. ... Outliers increase the variability in your data, which decreases statistical power. Consequently, excluding outliers can cause your results to become statistically significant.
When should I remove outliers?
It's important to investigate the nature of the outlier before deciding.
- If it is obvious that the outlier is due to incorrectly entered or measured data, you should drop the outlier: ...
- If the outlier does not change the results but does affect assumptions, you may drop the outlier.
Should outliers be removed or replaced?
Replacement involves swapping the data point for the mean or median of the sample. Many resources describe when to remove and when to replace. The bottom line: in most cases, it's recommended that you replace outlying conversion values and remove outlying visits and visitors.
