You are working with the text-only light edition of "H.Lohninger: Teach/Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999. ISBN 3-540-14743-8". Click here for further information.
| You are working with the text-only light edition of "H.Lohninger: Teach/Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999. ISBN 3-540-14743-8". Click here for further information.
|
Table of Contents  Appendix Exercises Design a Data Set: Outliers |
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| See also: survey of exercises, outlier tests |   |
The detection of outliers can be quite important, and cumbersome. To
gain experience in detecting outliers, you should design 2 data sets exhibiting
the following features:
| data set 1 | 700 to 1500 data points, normally distributed, no special measures against outliers taken (use the function "gauss" of the DataLab command Math/Transformation/Single Formula to create the data set) |
| data set 2 | approx. 1000 data points, skewed to the right (hint: use squared data of a normal distribution with a zero mean to create the skewed data). Change 2 values of the data set such that one of these values falls outside the +/-2.5 sigma range, but within the +/-4 sigma range, and the other falls outside the +/-4 sigma range. |
Apply the variance/iqr outlier test of DataLab and report the list of outliers.
Please answer the following questions:
You may now go directly to the 
in
order to experiment with the data.
Last Update: 2005-Jul-16