Have you considered normal probability plots (qqnorm) to identify outliers? These will identify much more, of course, including the need for transformations, mixtures of distributions, etc.

hope this helps. spencer graves

Monica Palaseanu-Lovejoy wrote:
Hi,

Thank you so much for all your rapid answers. I am impressed.

What i didn't know was that i have to assign my data to an object to work further on. It was not clear from the help (at least for me) that 'data()' itself is calling data already in R packages. All of you make that clear.

Now, if you can suggest any good package to use for identifying outliers it will be great ;-))

Hopefully from now one, since i understood how i am using the examples, what 'data()' means and how i am using my own data, i will put less trivial questions.

thank you so much indeed,

Monica


Monica Palaseanu-Lovejoy
University of Manchester
School of Geography
Mansfield Cooper Building Oxford Road, Manchester
M13 9PL, UK. email: [EMAIL PROTECTED]


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