# Quick and easy way to remove outliers

I have a set of data of locations and associated rent prices. Now there seem to be several outliers which I would like to get rid of so that a plot of my original data gains more meaning. In the "world" of statistics, would it be acceptable if I did this by eliminating any prices that who deviate from the mean by more than twice the standard deviation?

The aim of what I'm working on is to test out several machine learning techniques. I don't have to be extremely accurate but I wouldn't like to do something that is totally unacceptable.

• Please investigate some of the previous threads on the topic of removing outliers: you can find them by linking through the outlier tag. – whuber Nov 16 '13 at 15:40
• Outliers with respect to which model? "...would it be acceptable if..." -- acceptable to whom? What properties do you require? – Glen_b -Reinstate Monica Nov 16 '13 at 17:11
• you are dealing with a regression task. The hypothesis of your model pertain to the residuals (not to the $y$'s themselves). You should be wary of observations whose associated residuals are too far from the fit. The only reliable way to reveal such observations is in terms of their distances to a robust fit of your data. See this answer for more info – user603 Nov 17 '13 at 11:58