Abstract
One of the central questions in a legal trial is whether the suspect did or did not commit the crime. It will be apparent that absolute certainty cannot be attained. Because there is always a certain degree of uncertainty when interpreting the evidence, none of the evidence rules out all hypotheses except one. The central question should therefore be formulated in terms of probability. For instance, how probable is it that the suspect is the offender, given the situation and a number of inherent uncertain pieces of evidence? The answer to this question requires the estimation, and subsequent combination, of all relevant probabilities, and cannot be provided by the forensic expert. What the forensic expert can provide is just a piece of the puzzle: an estimate of the evidential value of her investigation. This evidential value is based on estimates of the probabilities of the evidence given at least two prespecified hypotheses. These probabilities can subsequently be used by the legal decision maker in order to determine an answer to the question above, but they are, of course, not sufficient. They need to be combined with all the other information in the case. A probabilistic framework to do this is the Likelihood Ratio approach for the interpretation of forensic evidence. In this chapter we will describe this framework.
Keywords
- Positive Test Result
- Crime Scene
- Glass Fragment
- Posterior Odds
- Forensic Evidence
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Stoel, R.D., Sjerps, M. (2012). Interpretation of Forensic Evidence. In: Roeser, S., Hillerbrand, R., Sandin, P., Peterson, M. (eds) Handbook of Risk Theory. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1433-5_6
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DOI: https://doi.org/10.1007/978-94-007-1433-5_6
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