# confusion on outliers

I am not able to distinguish the outliers - When to go with std. dev and When do we need to go with Median. My understanding on std. dev. is - if the data is away from mean by more than 2 std dev. we consider that as outlier. Similarly for Median, we say that any data that is not in-between q1 and q3, we say again that as outlier.

So am confused which one to choose.

Can you guys help me understand.

## 1 Answer

It completely depends on the context of the data that is being considered. For example, $$2\sigma$$ from the mean ($$\mu$$), depends on the distribution of the data. What is the value of $$\mathbb{P}(-2\sigma < X - \mu <2\sigma)$$.

Also, there are many methods for outlier detection, and all of them depend on the context. Hence, you cannot say which method should be used by taking it outside the context. You should do some experiments by these methods over the data, and then base on the real outliers sample, decide which method is proper for the current data.

• I understand that it depends on the context of the data but not sure on how to relate What should be used when? . I think if you can give a a real-time scenario , it would help. – AbdulWahab Khan Nov 20 '19 at 4:12