AND REFER TO THESE TEXTS, TITLE, AUTHOR, PAGES:

BACKGROUND READING:
- Forensic Science: 3rd edition Andrew R.W Jackson and Julie M. Jackson, Pearson 2011
- Criminalistics: An Introduction to Forensic Science, R.Saferstein, Prentice-Hall, 1998

SUBJECT SPECIFIC TEXTS:

THE EXPERT WITNESS IN THE CRIMINAL JUSTICE SYSTEM
- Criminal Litigation Handbook, M Hannibal and L Mountford: Oxford University Press 2010-2011
- Disclosure in Criminal Proceedings, D. Corker and Stephen Parkinson; Oxford University Press 2009
- Limitations of Expert Evidence, S Leadbeatter, ed, Royal College of Physicians, London, 1996
- The Role of Forensic Science Evidence in Criminal Proceedings,
- P Roberts and C Willmore, Research study No. 11 prepared for the 1993 Royal Commission on Criminal Justice, HMSO, London, 1993

THE USE OF STATISTICS IN THE ANALYSIS, INTERPRETATION AND EVALUATION OF EVIDENCE
- Essential Mathematics and Statistics for Forensic Science Adam, C, Wiley-Blackwell, Chichester, 2010 (an accessible text that covers both `traditional' and Bayesian statistical methods).
- Forensic Science: 3rd edition Andrew R.W Jackson and Julie M. Jackson, Pearson 2011(Chapter 13 and Section 3.7 of this edition is specifically concerned with statistics).
- Interpreting Evidence; Evaluating Forensic Science in the Court B Robertson and G A Vignaux, Wiley, Chichester, 1995 (a readable account of the Bayesian approach to evidence evaluation)
- Statistics and the Evaluation of Evidence for Forensic Scientists (2 edn), C G G Aitken and F Taroni, John Wiley and Sons 2004 (an advanced and comprehensive text)
- Science and Justice (references to specific papers will be given in the lectures and/or tutorials)

YOU MUST SATISFY THESE ADMISSION REQUIREMENTS:
Progress to level 6 of a forensic award

YOU WILL NEED ACCESS TO THESE RESOURCES:

Standard lecture room facilities, access to library and to computers with www and distributed learning access.
Blackboard VLE

THESE LEARNING STRATEGIES WILL OCCUPY YOUR TIME:

12x 2h lectures will be used to deliver the core material (sixteen hours on the legal and expert witness aspects of the module and the remainder on the statistical topics). Students will be asked to attend a session in court.
3 x 1h tutorials on the statistical aspects of this module.
In 123h of independent study time, you will consult the literature, especially in relation to carrying out research into the legal system and the application of statistics to the evaluation of evidence, either suggested by tutors or of your own choosing.

The court system and its personnel. The conduct of a case from investigation to verdict and appeal. The nature of adversarial justice and the process of proof within it. The rules of evidence. The role and responsibilities of the expert witness. Presenting evidence in court-examination and cross-examination. There will be lectures on presenting evidence in court by expert witnesses. Learning in earlier modules about the roles of Bayesian and non-Bayesian statistics in forensic science will be consolidated in this module. The fundamentals of statistical analysis will be revised and then buillt upon so that meaningful contrast can be made between the ability of Bayesian statistics to compare the individual with the population, and that of other statistical methods to compare samples, test for significance and explore trends in data. The roles of both Bayesian and non-Bayesian approaches to statistical analysis within the forensic science context will be examined. Students will be introduced to the Case Assessment and Interpretation model.

WHICH WILL BE ASSESSED BY:

Additional Assessment Information:
Students will be required to complete 2 pieces of summative assessment.
Outcomes 1 and 2 by an assignment set by the Law School. Exact details may vary from year to year but on all occasions students will be given details of what is expected. (70%)
Outcome 3 by end of module test (1h) (30%)

For the law element of the module, formative feedback is provided by the supply of self test questions after each lecture which are discussed as a whole group in the following lecture. Formative feedback for the statistical element of the module will be based on problem solving exercises and will be provided in the tutorial classes.