Finding Outliers using Interquartile Range | Statistics, IQR, Quartiles

How do we find outliers of a data set using the interquartile range? This is done using a simple rule, any value less than Q1-1.5*IQR is an outlier, and any value greater than Q3+1.5*IQR is an outlier. We'll go through the step by step process of finding outliers using IQR in today's video statistics lesson! #Statistics #APStats
Remember that a data value being an outlier doesn't suggest we should discard it; it means we should take a close look at it and decide what to do in our statistical analysis. We may want to discard it, it may be an error/typo in which case we would want to correct it if possible, or it may be a key to understanding the situation being analyzed!
Also, remember that if this rule doesn't identify a value as an outlier - that doesn't mean YOU don't think it is an outlier. If a data set is sufficiently small you can look at each value individually and determine what values merit special attention. This rule for outliers is particularly useful for large data sets; but we apply it to small data sets so we can practice applying it by hand and seeing it in action!
Interquartile Range vs Range of a Data Set: • IQR vs Range (interqua...
I hope you find this video helpful, and be sure to ask any questions down in the comments!
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The outro music is by a favorite musician of mine named Vallow, who, upon my request, kindly gave me permission to use his music in my outros. I usually put my own music in the outros, but I love Vallow's music, and wanted to share it with those of you watching. Please check out all of his wonderful work.
Vallow Bandcamp: vallow.bandcamp.com/
Vallow Spotify: open.spotify.com/artist/0fRtu...
Vallow SoundCloud: / benwatts-3
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[@zyphorx3604]

Thank you so much for this clarification! Helped me study for my RS1 progress check.

[@WrathofMath]

You're very welcome, I'm glad it helped!

[@inna7563]

Thank you so much for your SIMPLE AND DETAILED explanation! I understand the topic better now!!

[@WrathofMath]

Glad to help!

[@nargiskhan8734]

This was so helpful, Keep up the good work. Thank You.

[@WrathofMath]

Glad to help - thank you for watching!

[@nisritidris-said7809]

Thank you so much! btw I thought this was Sheldon from big bang explaining while watching.

[@WrathofMath]

You're very welcome, thanks for watching! I've heard that before, perhaps if they ever make an animated version of the show they can save money by hiring me for the voice acting! 😁

[@saemonne2123]

just too clear, been giving me hard time but after this video, its cool

[@WrathofMath]

Awesome, thanks for watching!

[@amiramulan3587]

Thanks, I needed this!!!!!!!!

[@WrathofMath]

Glad to help, thanks for watching!

[@rileyfayth]

Thank you 🙏🏽

[@WrathofMath]

My pleasure, thanks for watching!

[@tinni9242]

Hey...thanks for the explanation. Could you elaborate on the "1.5"? Any particular reason for this formula?

[@who813]

very helpful tysm!

[@WrathofMath]

Glad to hear it, thanks for watching!

[@Wedgeman_Riley]

when your doing your A-levels and have to come back to the basics

[@tivemajoroh8944]

Hey thanks for this! I was just wondering what if the two numbers are the same when calculating the median ? E,g 1,2,3,3,4,5 if the median is still 3 would I still include the other 3s in my first and third quartile ?

[@WrathofMath]

Depends on the length of the data list. In your example there is an even number of points, so we split it right down the middle, half the data to the left, half to the right. If the data set is odd, like 1, 2, 3, 3, 3, 4, 5, then we exclude the median, which is 3, and split the data across that median, so our lower half is 1, 2, 3, and our upper half is 3, 4, 5. The third 3, the one actually in the middle, is excluded.

[@tivemajoroh8944]

@@WrathofMath ahhh, fabulous thank you so much !

[@shadifm4767]

Thanks for explanation. Is it possible to not find any outliers in our data?! Because i did a test through this way and i didn’t have any value less than my lower bound and even not value greater than upper bound!

[@WrathofMath]

Thanks for watching and absolutely! It's perfectly normal to find no outliers.

[@superslim6528]

Thanks. However, what happens if I use 1/4(N+1)th value to find Q1, which gives 66 instead of 67? Could you kindly explain?

[@harshsomani6473]

Hi, this is late but when you get the 3.75th position you can just round up instead of finding a weighted mean.

[@davenhaven]

W