Can I exclude outliers when calculating mean or standard deviation (small-sample)? I am analyzing my results for a high-school biology paper. My data set consists of 20 groups in total, each having 4 repeats, so each is a small sample. I have a few (4) outliers that have a value lower than the control group (which is practically impossible and thus certainly the effect of a technical error).
Can I exclude the outliers when calculating the mean value or standard deviation, as they largely affect both parameters?
I am quite green when it comes to statistics, so I would hugely appreciate your help. Many thanks!
 A: Sometimes the outliers end up being of more interest than the rest of the data.  The discovery of penicillin was from studying the outlier.
Can you verify that the outliers are due to technical problems?  If you can show that they are impossible values then you have justification for not including them, or you may find something even more interesting when trying to figure out the unusual values.
The general recommendation these days is to not discard outliers without good, external reasons.  If you can throw out any values that you do not like, then you can make the remaining data say anything that you want, which is not good science.
If you still do not like the outliers, but cannot show the errors that caused them then you could analyze the data both with and without outliers and show how similar/different the results are.  There are also "robust" methods that are less affected by outliers that you could consider using (though you may need to consult with a statistician for those).
A: Excludding outliers is used in setting PAT Limits (PART AVERAGE TESTING) for automotive testing.  We want to throw the outlier away (Fail it) when calculating the Upper and Lower PAT limits.  The outlier would be logged as a failure and Binned as such.  Yes outliers are interesting, but not always necessary to keep in a distribution.
I have not determined how to do this. in Excel yet.
