Hi math people.


I'm in the process of analyzing some data that I collected through an experiment. The data are (somewhat) normally distributed and I represent the different data-sets using [boxplot](http://en.wikipedia.org/wiki/Box_plot), to provide an easy way of visually comparing the mean between the data-sets and the change in the variance.


In Matlab as default, the whiskers are used to represent all samples lying within 1.5 times the [IQR](http://en.wikipedia.org/wiki/Interquartile_range). According to Wikipedia on the boxplot, this is one of several way of using the whiskers. My question is simple why? What special significance does 1.5 times IQR have? Why not e.g. three times sigma?


(NB: I wanted to add the tags "matlab" and "boxplot", but I'm unable to create new tags.)



Why 1.5IQR whiskers in boxplot?
Three sigma has less relevance for asymmetric distributions. Using quartiles keeps it nonparametric. Regarding why not other quantiles of the distribution rather than 1.5\*IQR, you can follow some comments on this [thread](http://tolstoy.newcastle.edu.au/R/help/05/07/8210.html), which basically argues that you want to avoid specifying a fixed fraction of your data to be flagged as 'outliers'.


