# Boxplot Outliers

I'm looking for outliers in a non-normally distributed dataset:

• n: 1,900
• Mean: 2,738
• StDev: 1,544
• Min: 1
• Max: 22,102
• Anderson-darling: 40
• P < 0.005

The boxplot shows the outliers in one direction beyond upper extreme, but not the other way below lower extreme. Why is that?

Your variable is right skewed and probably bounded to be positive. This is maybe easiest to see in graphs:

You can see that in the skewed graphs the outliers are all on one side.

For those who are interested: I created that graph in Stata using the following code:

clear all
set seed 1234567
set obs 4
gen distribution = _n
label define dist 1 "normal"       ///
2 "fat tails"    ///
3 "right skewed" ///
4 "left skewed"
label value distribution dist
expand 1000
gen x     =  rnormal() if dist == 1
replace x =  rt(4)     if dist == 2
replace x =  rchi2(2)  if dist == 3
replace x = -rchi2(2)  if dist == 4

stripplot x , over(dist)           ///
stack width(0.5)     ///
box(barw(0.2)) iqr   ///
boffset(-0.3) h(0.5)

• Maarten, there is no doubt that the single-, double-, and some triple-digit values in my dataset are outliers. Is it prudent to just manually remove these and re-run the boxplot? – Harper Jun 21 '16 at 11:36
• Outliers aren't necesserily bad. If they are typos, then by all means drop them, but if they are genuine observations then dropping them would be bad. – Maarten Buis Jun 21 '16 at 14:17