- Docente: Susi Pelotti
- Credits: 1
- SSD: MED/43
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Single cycle degree programme (LMCU) in Law (cod. 9232)
Learning outcomes
At the end of the course the student has the opportunity to understand and apply elements of probability theory and decision theory to solve the problems that arise in the interpretation of scientific data in the procedural field; understand and explain the development of likelihood ratio formulas for evaluating the forensic information from which the decision is derived; apply the theoretical framework to analyze and understand the problems that arise in the case studies, emerging in the application of forensic science to law, and know and know how to apply IT tools (graphic models) useful for analyzing the aspects of inference and decision-making in the legal field .
Course contents
The scientificevidence
probability theory and decision theory
LR in forensic genetics
LR in forensic pathology
the interpretation of the activity level DNA
Bayesian networks
Readings/Bibliography
Samie L, Champod C, Taylor D, Taroni F. The use of Bayesian Networks and simulation methods to identify the variables impacting the value of evidence assessed under activity level propositions in stabbing cases. Forensic Sci Int Genet. 2020 Sep;48:
Bayesian networks for probabilistic inference and decision analysis in forensic science, 2014
Coherently updating degrees of belief: Radical Probabilism, the generalization of Bayes' Theorem and its consequences on evidence evaluation [https://philpapers.org/rec/TARCUD]with Paolo Garbolino and Silvia BozzaLaw, Probability and Risk 19 (3-4): 293-316. 2021.
Teaching methods
lessons
application in casework
Assessment methods
case solving
oral examination
Teaching tools
slides
software
Office hours
See the website of Susi Pelotti