I have a dataset with a column on which I can apply outlier removal logic of box-plot (all rows with value lower than (Q1 - 1.5 x IQR) and higher than lower than (Q3 + 1.5 x IQR). However, it is observed that after removing outliers, if the box-plot is plotted again and outliers are detected and removed using the same logic, some additional rows are also eliminated. This process can be repeated multiple times till no additional rows are removed even after applying this logic.
My queries are:
- What does it mean when additional rows are removed when box-plot is made again and new outliers are found?
- Should outliers be removed only once or should we repeat the process till there are no more removals?
- Are there any recognized studies / papers / journal articles which have studied this?
