Condition Fingerprint experts Novices Match 92.12% 74.55% Similar Distracter 99.32% 44.82% Non-similar Distracter 100.00% 77.03% Source: Tangen, J.M., et al. "Identifying fingerprint expertise", Psychological Science, Vol. 22, No. 8, August, 2011(Figure 1).
Fingerprint expertise. Software engineers are working on
developing a fully automated fingerprint identification algorithm. Currently, expert examiners are required to identify the person who left the fingerprint. A study published
in Psychological Science (August, 2011) tested the accuracy of experts and novices in identifying fingerprints.
Participants were presented pairs of fingerprints and asked
to judge whether the prints in each pair matched. The pairs
were presented under three different conditions: prints
from the same individual (match condition), non-matching but similar prints (similar distracter condition), and nonmatching and very dissimilar prints (non-similar distracter condition). The percentages of correct decisions made by the two groups under each of the three conditions
are listed in the table.
a. Given a pair of matched prints, what is the probability
that an expert will fail to identify the match?
b. Given a pair of matched prints, what is the probability
that a novice will fail to identify the match?
c. Assume the study included 10 participants, 5 experts
and 5 novices. Suppose that a pair of matched prints are
presented to a randomly selected study participant and
the participant fails to identify the match. Is the participant more likely to be an expert or a novice?
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