Dealing with Outliers (part 2)

[@firatkurt4289]

I learn a lot from your videos..thank you..

[@AlNova01]

Thanks for this video. It was very informative. On a separate note, at around minute 2.47, you mentioned the use of bootstrapping to work with data that may be affected by too many outliers. . I will be interested in seeing some video series where you explain the use of bootstrapping for correlation and for linear regression when data is non-normally distributed.

[@ihabibrahim2000]

The video is very useful . Thanks alot

[@charlottebell334]

Thank you. Your videos have been very useful, but just one question. Elsewhere I have heard people so that you can use the average for the outlier. Can you compare/contrast and clarify the differences between using that and winsorizing please. Thanks.

[@how2stats]

I've never heard of someone using the average in this context. People sometimes use the average for replacing missing values.

[@Azam_Pakistan]

Yes someone told me too to take moving average

[@eefje751]

Very helpful video! Which of the three references can I use to verify my choice for winsorizing? Thanks.

[@viacheslavchepkasov1199]

Thanks a lot, it is very useful :)

[@fleurli2782]

2 out of 5, would it be 40% winsorizing?

[@fakuridesne]

2 out of 10 . not 5

[@itismetomnl]

@@fakuridesne From where do you get 10?

[@phumzilemahlangu6629]

Thank you for such a great video, I am learning alot from your videos. Just one question, which R code can I use to winsorize my data?

[@samar3634]

Thank you this video is very useful

[@franccezco]

Nice video, thanks!

[@languageandmana9255]

👌👌👌