Generalized ESD Test for Outlier Detection using Python
The Generalized Extreme Studentized Deviate (ESD) Test is a statistical test for outliers. It is used on univariate data which follows an approximately normal distribution, and can be used to detect one or more outliers.
It is especially useful in situations where the number of outliers is not known: in other outlier tests, like the Grubbs test and the Tietjen Moore test, the number of outliers to be found must be specified beforehand. For the ESD test, you just specify an upper bound for the number of outliers.
We test the null hypothesis that the data has no outliers vs. the alternative hypothesis that there are at most k outliers (for some user specified value of k).
Grubb's Test Video : • Grubbs Test for Outlier Detection using Py...
Link to the Notebook :
https://github.com/bhattbhavesh91/out...
If you do have any questions with what we covered in this video then feel free to ask in the comment section below & I'll do my best to answer those.
If you enjoy these tutorials & would like to support them then the easiest way is to simply like the video & give it a thumbs up & also it's a huge help to share these videos with anyone who you think would find them useful.
Please consider clicking the SUBSCRIBE button to be notified for future videos & thank you all for watching.
You can find me on:
Blog - http://bhattbhavesh91.github.io
Twitter - / _bhaveshbhatt
GitHub - https://github.com/bhattbhavesh91
Medium - / bhattbhavesh91
#GeneralizedESDTest #ESDTest #Outlier #GrubbsTest