Outlier Removal

The distributions of each parameter will be searched for outliers according to a method of choice and rows containing outliers will be removed.


The method to determine the lower and upper bounds of the data (outlier limits). Mean +- SD: This assumes a normal distribution. outliers are defined to be greater than "Mean + Factor*SD" or smaller than "Mean - Factor*SD". Factor is 3 per default. Boxplot: outliers are defined to be greater than "Q85+Factor*IQR" or smaller than "Q25 - Factor*IQR", where Q are the quantiles and IQR is the inter quantile range. Be careful the default 3 goes with the default method (Mean +- SD). A standard value for this method would be 1.5.
The factor multiplies the value describing the spread of the distribution.
Select the columns by which the measurements should be grouped (example: plates, batches, runs...)
The first column filter allows to select multiple columns to define groups. Rows that share the same values for all constraint columns belong to one and the same group.
The second column filter is to select the paramters where the values have to be ckecked for outliers.
All Parameter
Per default unchecked. In this case an row is removed if it has an outlier value for at least one parameter. If you tick this checkbox, the row is only removed if all the values for all parameter are outliers.

Input Ports

data for outlier analysis

Output Ports

table with outlier rows removed.
No description for this port available.


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