Thank you for this video. Years later and it is still helpful.
@macacoman7 жыл бұрын
This is one of my favorite channels on youtube! Thorough yet clear. Keep up the good work man!
@lisaheaney314 жыл бұрын
Thanks for providing citations! Really helpful.
@AnelyBek3 жыл бұрын
Thank you Dr. How2stats!
@yvesburtworthington32447 жыл бұрын
Thanks you for helping me with my homework in Advanced Statistics
@anitacarrier93862 жыл бұрын
My lecturer told me not to use box plots to check for outliers as it only uses the median and interquatile range rather than the mean, he then advised me to create z-scores to find outliers as this is based on the mean, however, he only showed us how to do that manually and not with spss.
@dsavkay5 ай бұрын
Thanks, great insight! 💯
@willjfit93453 жыл бұрын
How do you remove the outliers?
@gabitroyano4 жыл бұрын
Thank you for the explanation! It's very good and simple! Thanks a lot!
@tsehayneshgedefew53102 жыл бұрын
I do have two questions.first is it mandatory to check normality for individual contnious variables or one by one secondly can we check normality of our data after coding?
@snakeyjake75 жыл бұрын
Really helpful, informative and to the point. Thanks!
@vbeija7 жыл бұрын
Thank you for the instructions and references.
@nargisali72983 жыл бұрын
In multivariate analysis, a Zscore = 3.2 would be an outlier if the data set contain 1000 cases?
@YooBro2193 жыл бұрын
Sir you the GREAT
@SaadKhanYousafzai7 жыл бұрын
Hi there. First of all I have to thank you for such amazing videos. Secondly I have a problem and I have tried hard to find a solution but all in vain. I had some missing data and on top of it I also removed few outliers. I have multiple variables for single subject. I tried to do a repeated measure ANOVA but just because of one missing variable for a subject, all other variables are also ignored and I am loosing subjects. A had 23 subjects but ANOVA analyze just 14. If I put ZERO in missing varaible's place it gives me lower MEAN value. Please tell me how to fix the missing data so I can analyse all the subjects and it should also not affect my MEANS for all the varaibles. P.S: I can not to any computation method (I have seen your MCAR videos) to predict the values. It will mess up my data very bad.
@ricardovonschoettler4 жыл бұрын
Thanks for the video, it has helped me in my research work. But if I have a query, in the case of time series, if we want to assess normality, should this be done only on the component called "noise"? Thanks
@alexsisccdr7 жыл бұрын
Great videos. Where can I get the Excel you are using to calculate outliers based on the 2.2 multiplier?
@saro47617 жыл бұрын
Thanks so much for this valuable information
@RajeshChaudhary3 жыл бұрын
It would be great to know about a technique in SPSS to identify an outlier based on standard deviation. Could you please guide on this?
@mittadileepkumar37567 жыл бұрын
Thank you so much for an amazing explanation. :)
@kyrank.43216 жыл бұрын
Thanks, this was very helpful
@slsmithy80756 жыл бұрын
Hi, probably a dumb questions, but when you go from the Var1 data set to Var2 data set, what would you call the "error bars" in the var2 graph, because technically the top error bar isnt the "maximum" as the "maximum" is the outlier. Thanks.
@how2stats6 жыл бұрын
It's a fine question. They correspond to the 25th (low bar or lower quartile) and 75th (high bar or upper quartile) percentiles.
@slsmithy80756 жыл бұрын
@@how2stats I thought the 25th and 75th percentile were the top and bottom lines of the box? Im asking what would you call the error bar above and below the box, given the outlier is the 'maximum'.
@kritikadmonty89914 жыл бұрын
Can we use the method of labelling outliers for non-normal data ? If not how do we identify outlier in non normal data?
@how2stats4 жыл бұрын
Depends on how non-normal the distribution is. I'd say skew less than .50 should be fine. There are outlier detection methods for non-normal distributions, but I haven't learned them yet!
@milenah22275 жыл бұрын
Good work, thank you for the video! But I've got the problem that my variable is metric with a huge range from 3 to 12 000 000, that is why I can't detect the extreme outliers (multiplier 3.0) visually in the boxplot visualization. The scale is too wide to identify the values that are too low. How can I solve that problem?
@how2stats5 жыл бұрын
Extreme outliers can distort the visual appeal of a box plot. You might consider simply reporting that the value of 12 000 000 was an outlier and dealt with (either removed or Winsorised). Then, re-do the box plot.
@ThePookie257 жыл бұрын
Thank you for this!
@komaljerawla56994 жыл бұрын
once you detect an outlier what do you do next? do v remove it from the data set?
@how2stats4 жыл бұрын
Good question. I usually winsorize it: kzbin.info/www/bejne/jXvYc2Osj9VprZY
@diogotalhinhas11462 жыл бұрын
muy bueno
@shaunlikescheese6 жыл бұрын
Does the 2.2 multiplier break down at all when applied to larger data sets? Say, n = 600?
@how2stats6 жыл бұрын
Yes. I'd use 2.2 multiplier for samples between 20 and 300. Thereafter, I'd use a multiplier of 3.0.
@shaunlikescheese6 жыл бұрын
Is there research supporting this though?
@how2stats6 жыл бұрын
Yes, check out Hoaglin's research; he might say it in this paper: Hoaglin, D. C., Iglewicz, B., & Tukey, J. W. (1986). Performance of some resistant rules for outlier labeling. Journal of the American Statistical Association, 81(396), 991-999. Or another paper in that time period.
@devez75 жыл бұрын
so how do u choose the 3 multiplier? u did the same thing
@how2stats5 жыл бұрын
You don't have to "choose" anything. SPSS automatically reports results with the 1.5 and 3.0 multipliers (circles and stars, respectively).