|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|
|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