Outliers -- 1.5 x IQR (Improved!)
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- Опубліковано 11 вер 2024
- This video outlines the process for determining outliers via the 1.5 x IQR rule. This is the second version of this video--same audio as previous video, but my visual skills are improving!
Simple and spot on when explaining the negative component of an outlier, if it is present. This is not explained in most other videos, Thanks Kelly
Great explanation! Thank you for such a short and to-the point video. :)
This was much easier to understand than random information. Thank you.
Cheers girl, I'd be dead without this!
Why 1.5 factor? can you please explain what is the mathematical rational for this value?
+Ishai Perelman For outlier detection we use box plot isn't it. And box plot was invented by J. Tukey in 1977. He only has placed 1.5 * IQR as the demarkation of outliers in the box plot ( or box-and-whisker plot ) which we see in the plot. I hope this is convincing :)
Great video! Easy and concise!
Omg you explain so clear thank you so much..😍
Thanks for making this very simple
and quick
So in order to find IQR TIMES 1.5 JUST MULTIPLY that's all??
Isn't that for finding outliers?
Thank you!
Very helpful video
THANKS!
How does the outlier effect the IQR?
Do u mean how does the IQR effect the outlier? Because the IQR determines the distance between Q3 and the boundary and Q2 and the boundary to get the outlier, if that makes any sense?
Thank You
way to use an even number of observations...
Wait I dont get it :/ Why is Q1 =1.5 and not 1. 1 is the 3rd number in 12 numbers, just like Q3 should be 40...
To find Q1, you have to take the median of the first half of the numbers. Since there are 6 in the first half, there is no middle number. Instead you average the 3rd and 4th. Same with Q4, but with the second half.
kelly castaneda ah okay thanks
Merci!!:)
Hey 704!
Mohammed Sillah mohammed-🤣
wtf