Answer / Rakesh

An outlier is a data point that significantly differs from other data points in the same dataset. Outliers can be caused by errors, noise, or rare events. Treatment of outlier data depends on their cause and impact on analysis: 1) If they are due to measurement errors, they should be corrected if possible. 2) If they represent rare but valid events, they can be kept as is but flagged for further investigation. 3) If they have a significant impact on the results, various techniques like Winsorizing (replacing extreme values with less extreme ones), robust regression, or clustering can be used to handle outliers.

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