The following explains the probability tables used for the two chance
nodes Murderer? and DNA-match? used in the murder
network.
The Murderer? node
In the presented case, Colombo knew for sure that the killer was
member of a well defined group. In our model we assume that the killer
is known to be from Denmark. The Danish population is approximately 5
millions. By picking a random individual from the street the
probability of him (or her) being the murderer becomes as in Table 1.
Murderer?="yes" |
Murderer?="no" |
1 |
4,999,999 |
|
Table 1: Cpt of the Murderer? node. |
The DNA-match? Node
DNA typing of biological material has become one of the most powerful
tools for personal identification in criminal investigations. The
problem with DNA analysis lies in determining whether two
DNA-fingerprints match. A match conclusion is therefore always
accompanied by a probability of obtaining a match as good as that
found in the evidence. This probability depends highly on the quality
of the biological stain recovered from the scene of the crime but also
on the frequency of the elements in the fingerprint occuring in the
population. This indicates that even if a person is innocent his
genetic fingerprint can be "similar" to the one extracted from the
biological stain found at the scene of the crime.
In our model we assume that if the individual really is the killer the
DNA fingerprint will match. Colombo is informed by the forensic
experts that the quality of the recovered stain results in a 1/100000
chance of obtaining a coinciding match. Hence the probabilities for
the node are given as in Table 2 .
|
Murderer?="yes" |
Murderer?="no" |
DNA-match?="yes" |
1 |
1 |
DNA-match?="no" |
0 |
99999 |
|
Table 2: Cpt of the DNA-match? node. |