Question

Extreme values in statistics most of the times can be troublesome. If a data point is so extreme compared to the rest of the data (i.e. unusually high or unusually low), then the first thing to do as a researcher is to double-check and see if there is no mal-function of the equipment in use, or there is no recording error, or there is no unusual thing happening . ..that doesn't reflect the norms of the distribution of the data. If it does, we need to see how extreme an observation is to be considered as an outlier. 1) Briefly discuss how to detect outliers under different scenarios....assuming symmetry then with the absence of symmetry. What impact, if there is any, do they have on the model?

Answer 1

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Answer

There are lot of procedures are exist to detect outliers such a PCA ( Principal Component Analysis),

HiCS (High Contrast Subspaces for Density-Based Outlier Ranking) , Cook distance etc. Here I am giving some simplest and easy method to detect outliers on symmetrical as well as Non-Symmetrical cases..