Grubbs

Outlier test based on the assumption that the data is normally distributed.

The steps to follow are:

Define the average of the first 20 Datapoints; ( Average( Reeks));
Define the standard deviation of the 20 Datapoints; ( StDev.s( Reeks));
Define per Datapoint the absolute difference between the datapoint and the average;
Define G per Datapoint. G is the absolute difference from point 3 divided by the standard deviation from point 2;
The Datapoint is an outlier when G exceeds the critical value of 3,001.
Choose the outlier with the highest G in case there are multiple outliers.

The critical value for 20 observations with a confidence level of 95% is 3,001

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