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 Forged Banknotes |
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| See also: linear discriminant analysis |   |
Suppose
you are the manager of a bank and you have the problem of discriminating
between genuine and counterfeit banknotes. On the left you see a banknote
worth 1000 Austrian schillings (about 72.67 Euro). You are measuring several
distances on the banknote and the width and height of it. Measuring these
values of about 100 genuine and 100 counterfeit banknotes, you will finally
end up with a table of 200 observations with several variables.
Use the data set FLURIEDW to
set up a model which is based on linear discriminant analysis and is capable
of discriminating between genuine and counterfeit money (this data set
contains data on Swiss francs; it has been obtained courtesy of H. Riedwyl
[Flury 1983]). Use 
to calculate the model.
Use the calculated model to find out which of the following bank notes are counterfeit:
Length Left Right Bottom Top Diagonal
BN1 215.1 130.0 129.8 9.1 10.2 141.5
BN2 214.7 130.7 130.8 11.2 11.2 139.4
BN3 214.3 129.9 129.9 10.2 11.5 139.6
BN4 214.7 130.0 129.4 7.8 10.0 141.2
You may directly load the data of these four banknotes into and
apply the stored discriminating model.
Last Update: 2005-Jul-16