Video není dostupné.
Omlouváme se.
The Right Way to Detect Outliers - Outlier Labeling Rule (part 1)
Vložit
- čas přidán 18. 08. 2024
- I demonstrate arguably the most valid way to detect outliers in data that roughly correspond to a normal distribution: the outlier labeling rule. I also point out that using 2.2 rather than the more common 1.5 is more appropriate as a multiplier.
The formulae I use in the video are:
Upper = Q3 + (2.2 * (Q3 - Q1))
Lower = Q1 -- (2.2 * (Q3 - Q1))
The references in video are:
Tukey, J.W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley.
Hoaglin, D.C., Iglewicz, B., and Tukey, J.W. (1986). Performance of some resistant rules for outlier labeling, Journal of American Statistical Association, 81, 991-999.
Hoaglin, D. C., and Iglewicz, B. (1987), Fine tuning some resistant rules for outlier labeling, Journal of American Statistical Association, 82, 1147-1149.
"outliers statistics" "statistical outlier"
I don't think you fully comprehend HOW HELPFUL YOU AND YOUR VIDEOS ARE!!!!
Thank you so much!!
I don't think you fully comprehend HOW HELPFUL YOU AND YOUR VIDEOS ARE!!!! (still true)
if you havent already brought out a book- please do!!!!
this helped me way more than any book ive tried to decipher. thank you!!!
Great ! Thank you for the nice solution for detecting outliers systematically !
What about non normal distribution?
God I hope I find this video soon - my data is totally non parametric!
you mentioned in the video a method for non-normally distributed data. Can you give some clues?
Do you have and can you test for outliers when dealing with categorical data? Thank you.
Hmm...why are my box plots and histograms blue instead of the color in the video?
thank you so much...your videos are very helpful :)
Thanks. Very useful.
Hello,
Thanks for creating this video! :) Is there a reference citation for the Outlier Labeling Rule?
The references are in the description of the video.
if i have multiple scale scores from the same sample, what variable do i put in? the total raw score? the individual questions? do i put them all, or do i do this for every scale in particular?
thanks a lot sir it was a helpful video
What multiplyer does SPSS use to calculate outliers? I know the norm is either 1.5 or 2.2 but I need to calculate my outliers at 3 times the IQR to the left and right of the first and third quartiles. Is there a way to change this setting in SPSS so that I can get a Box and Whiskers plot that shows the outliers with the 3* instead of what ever SPSS uses as its standard multiplyer?
Hey thanks for the video - may I ask what if the score is minus?
Hey, every time I do a lineair regression, my model keeps giving me new casewise diagnotics. My KS-test is under 0.2. Can you please help me? We have already made dummies and of our independent we made a LN
Thank you very much.
Is there anyone know what is the name of this method (for example: Mahalanobis , The Variance-Covariance Matrix, Fast-MCD Algorithm, .... etc)
please tell which software package you used for creating your data (normal and non-normal)??
thanks for the info.
my data has academic achievement as dependent variable and intelligence as independent....i should calculate outliers w.r.t.achievement or intelligence??
+tabi151214 Both variables need to be examined for outliers.
can you please share with us sample data
What if my data is not normally distributed?
+Onomato Poet Consider using bootstrapping for your test statistic
+how2stats How does that work?
I really really appreciate these videos. If you would like some constructive criticism, you tend to smack your lips a lot, it might be a good idea to pay attention to that while recording. Thanks once again!
What ever your doing your statistical analysis upon. If you're only going to analyse the total score, then you only need to look for outliers there. But if you plan on doing analyses at the item level, then you should look for outliers there too. I doubt you'll find outliers at the item level.
who came up with the outlier formula? maybe we've been throwing out important data this whole time!