Removing Outliers Criteria

Hi,

Why are outliers being removed randomly instead of using statistical methods? In general, the outlier’s parameters are defined the following way:

  • q3+IQR*1.5
  • q1-IQR*1.5

Instead, what I’m seeing is that people are removing values based on their personal criteria.

Hi @santoshector421:

You provided a tag to a guided project. May I know which particular project you are referring to? Please include a question link as per these guidelines if there is indeed a mission link.

If there are several outliers (>7) I will usually stick with this. For data will fewer outliers, I would suggest removing them if those data points are not really critical. In a mission critical project where you have to deploy the model/process data to build a model etc., then I would replace the outliers with the central tendency values not counting the outliers (mean, median or mode) after conducting my EDA since the data points may matter.

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