iSixSigma

Outlier

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  • #24869

    Sloan
    Participant

    Hod do i find an outlier in a non-normal distribution?

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    #59654

    Remi
    Participant

    Hai Outlier,
    distributions don’t have outliers, whether normal or not.
    If you mean “how can I see if a data-point is an outlier in a data set that does not follow a normal distribution”:
    – make a graph (dotplot, histogram,…)
    – if you see a point ‘far away’ (purely subjective eyeball mark1 measurement) investigate WHY that point is different (find the physical reason, not mathematical)Hint: especially the boxplot works well for this; points ‘far away’ are marked as seperate stars in the graph.If you know WHY you can decide wheter to remove it from the data set or not. And redo with the reduced data set
    – check if the data set fits any known non-normal distribution (with and without the suspicious point). Look up for that distribution when points are suspected to be outliers and find out WHY again.
    Hope this helps,
    Remi

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    #59658

    Sloan
    Participant

    Hi Remi,
    thanks for the post..doesnt box plot also assume normality while indicating outliers….guess 1.5IQR goes beyond 3 sigma hence identified as outlier….is there any other statistical estimate……
    Reg
     

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    #59659

    Remi
    Participant

    Hi outlier,
    No, Boxplot does not use normality; it is distribution free.  What happens is: IF Data is Normal distr. THEN (1.5*IQR and 3* Stdev give the same value) and (Median and Mean give the same value). So in that case points further than 1.5*IQR happen to cross the +/- 3S line.For detecting potential outliers mathematicians have calculated what a treshold could be: the 1.5*IQR of boxplot and UCL/LCL of contral chart are just these. But remember: the treshold indicates only that “an occurence like this is very unlikely to happen (in a stable situation) so when it happens we should investigate if there is a special cause for it to happen”.If you have multiple populations (e.g. batches with shifted Mu) or a changing variation over time (e.g. heavy wear) the calculation goes wrong because the situation is not stable.There is no formula for ‘ís this an outlier?’
    Remi

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