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Mar 19 at 8:47 review Close votes
Mar 19 at 13:17
Mar 18 at 15:34 comment added Peter Flom Although I agree with @whuber that this is really an algebra problem, I think it should stay open (and I don't see any close votes) because the comments and answers have useful statistical content.
Mar 18 at 15:17 answer added Peter Flom timeline score: 4
Mar 18 at 15:00 comment added whuber Welcome to CV, Bongo. There's actually no statistical content to this question (not your fault) and its answer will be of little value, because it's just an algebra problem in disguise. Moreover, this definition of "outlier" is not only questionable, it's idiosyncratic: the original formula for the upper boundary was $x_4 + 1.5(x_4-x_2),$ which will indeed highlight a sufficiently large value of $x_5$ for further examination: that is, as an "outlier." I would therefore suggest finding a different resource for learning this material.
Mar 18 at 14:23 history edited Bongo 186
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Mar 18 at 14:16 comment added Stephan Kolassa That said, look at the formula for "upper outliers" and simplify it. Which of your data points would be a candidate for an "upper outlier"? What relation would it need to satisfy, given the (simplified) formula? Can it satisfy this relation?
Mar 18 at 14:15 comment added Stephan Kolassa The entire concept of "outliers" is very dubious. I believe I am not saying too much if I state that the consensus here is that "outliers", as defined by this formula, should not, e.g., be blindly removed. The formula you are looking for is a tool to determine which data points should be plotted how in a boxplot - nothing more.
Mar 18 at 14:14 comment added Stephan Kolassa Please add the self-study tag & read its wiki.
S Mar 18 at 14:09 review First questions
Mar 18 at 16:32
S Mar 18 at 14:09 history asked Bongo 186 CC BY-SA 4.0