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.
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| See also: autocorrelation function |   |
One phenomenon which can be particularly misleading is autocorrelation. The term serial correlation is sometimes used for autocorrelation. Autocorrelation means correlation between successive values in the data. It mainly occurs when data is measured over time, and the values are not independent of each other. Please note, that most inferential tests and modeling techniques fail if data is autocorrelated.
The figure below shows a data set exhibiting serial correlation. As you can see, serial correlation can be easily recognized just by looking at the data.
In contrast to the figure above, the following figure shows a signal
which exhibits no autocorrelation.
In order to get a more objective measure of serial correlations, one
should calculate the autocorrelation function.
Last Update: 2004-Jul-03