Forensic Statistics and DNA-evidence

Course manual 2024/2025

Course content

Forensic Statistics is relevant for all forensic disciplines and the Bayesian paradigm connects them. The area where this is most pronounced and most developed is DNA evidence. For this reason, the focus of the course will be on DNA and biological trace evidence, but applications of forensic statistics in other areas will also be considered.

This Course has two main topics:

1. The biology and genetics of DNA-evidence, as well as the current methods for the analysis  and interpretation of DNA traces:
2. The forensic statistical methods used for the evaluation and combination of (biological) evidence, both at source and activity level.

The Bayesian paradigm for computation of the value of evidence is applied to DNA evidence of increasing complexity, ranging from single source profiles to more complicated DNA evidence such as DNA mixtures and low template DNA profiles.  The issues covered will include: DNA database searches, Kinship analysis and Disaster Victim identification (DVI), Bayesian Networks for Activity level evaluation and the combination of multiple evidence, and Familial Searching.

Study materials

Literature

• Butler, J. (2005) Forensic DNA typing biology, technology, and genetics of STR markers . 2nd ed. London: Elsevier Academic Press.

• Aitken and Taroni. Statistics and the Evaluation of Evidence for Forensic Scientists. John Wiley And Sons Ltd., Third edition 2020

• Butler, J. (2011) Advanced topics in forensic DNA typing: methodology. Academic Press.

• Jackson, Andrew R. W., and Julie M. Jackson. Forensic Science. Fourth edition. Harlow: Pearson Education Limited, 2017. Print, chapter 6

• Butler, J. M. (2015). Advanced topics in forensic dna typing : interpretation. Oxford, England ;: Academic Press.

• Banks et al. (2021) Handbook of forensic statistic

• Buckleton et al. (2016) Forensic DNA evidence interpretation. Taylor and Francis

• Primorac, Dragan, and Moses Schanfield (2023) Forensic DNA Applications : An Interdisciplinary Perspective. 2nd ed. Oxford: Taylor & Francis Group

• D. Taylor and B. Kokshoorn (2023) Forensic DNA trace evidence interpretation

Objectives

• 1. apply knowledge of forensic biology, biological trace examination and DNA-analysis to problems from crime scene, identification and individualization of biological evidence.
• 2. assess given cases involving standard DNA profiles, mixtures, relatedness issues and database search by applying the Bayesian paradigm and interpreting the results.
• 3. explain the concept of validating forensic interpretation methods.
• 4. assess and evaluate activity-level questions or a combination of evidence through the application of Bayesian networks.
• 5. assess problems of Kinship, relatedness in pedigrees, DVI and Familial searching by setting up and applying the relevant statistical analysis.
• 6. evaluate a comprehensive request for examination of biological trace evidence and to formulate hypotheses and alternative hypotheses at activity level.
• 7. evaluate the evidential strength of complex DNA profiles using (semi) continuous statistical tools.
• 8. recognise and avoid common fallacies in the interpretation of evidence (with emphasis on prosecutor and defence fallacies).

Teaching methods

• Lecture
• Self-study
• Presentation/symposium
• Computer lab session/practical training

Lectures, tutorials consisting of exercises, mock crime scenes, report writing on the basis of mock and real laboratory data (DNA profiles) and group presentations of studied literature.

Learning activities

Attendance

This programme does not have requirements concerning attendance (OER part B).

Additional requirements for this course:

Attending all scheduled education activities is strongly advised. By doing so, you actively contribute to a lively learning community and significantly improve your chances of successfully completing the course. The designated mandatory activities play a crucial role in achieving the course objectives and are essential for your overall progress.

Assessment

All components will be graded on a scale from 1 to 10, with a maximum of one decimal after the point. These grades are used to calculate the final grade. In order to pass the course, all components and the final grade have to be sufficient, i.e. at least a five and a half. When a student has not fulfilled this requirement, the examiner will register the mark ‘did not fulfill all requirements’ (NAV) whether or not the averaged grade is sufficient.

The components will be weighted as follows:

1. Bayesian Framework assignment (10%).
2. Group assignment on Bayesian networks (15%).
3. Group assignment mixture analysis (0%; not graded).
4. Group presentations on biological topics (DNA typing)(10%).
5. Individual DVI assignment, to hand in at the final exam (15%)
6. Final exam (50%)
   

   
   Assignments 1 and 2 together cover statistical topics (for 25%). Assignments 4 and 5 cover topics in forensic biology (for 25%). Assignment 3 is not handed in; correct answer is given in tutorial session.

   The exam of this course will be a written examination (open book exam) based on the content covered during the lectures. The exam consists of two parts, a part about the biology in the course and a part about the statistical aspects of DNA analysis. The biology part counts for 40% of the  score for the exam, while the statistics part counts for 60%. 

   The final grade will be announced at the latest on 17th of April (= 15 working days after the final course activity). Between the 17th of April and May 20th (= 35 working days after the final course activity) a post-exam discussion or inspection moment will be planned. This will be announced on Canvas and/or via email.
   
   

   
   Table of specification

   		Exit qualifications
   Learning outcome	Components (see above)	1	2	3	4	5	6	7	8	9	10
   1	4, 6		x
   2	1, 3, 6			x
   3	6			x
   4	2			x
   5	5, 6			x
   6	2, 6			x
   7	6			x
   8	6						x

   Table 1: Table of specification: the relation between the learning outcomes of the course, the assessment components of the course and the exit qualifications of the Master’s Forensic Science (described in the Introduction in the Course Catalogue). 

Assignments

The students will be (randomly) divided in groups of five students. Assignments 2 and 4 will be done in groups and graded as such. Assignments 1 and 5 will be individual and will be so graded. Assignment 3 will be done in a group and will not be graded.

1        Bayesian Framework assignment

During the course the so called Island problem will be reviewed. In the lecture notes there are some exercises concerning this type of problems. The students will be given one such exercise  a solution of which they have to hand in individually. The solutions will be graded on a scale of one to ten.

2         Group assignment Bayesian Networks

The theory of Bayesian networks will be done during a lecture. For this assignment the students are working in groups of about five. There will be an introduction to the program HUGIN, a program to analyse Bayesian networks. The groups will be given a certain practical situation where a network can be built. The groups have to make their own network in HUGIN and motivate their choices. The solutions will be graded on a scale of one to ten.

3         Group assignment mixture analysis

The theory of analysis of mixtures will be done during a lecture. The assignment consists of performing an analysis of a DNA sample using computer software for the calculation of the evidential strength of DNA mixtures.

4         Group presentation

The students will be divided in groups of about five. Each group is assigigned to a topic on DNA typing techniques. The group selects a relevant scientific publication or case review on this topic and prepares a presentation on their findings. The presentations are graded with the assessment form in the appendix.

5         Individual DVI assignment

This is an individual assignment where the students are given DNA profiles of  unidentified victims in a mass grave and a list of DNA profiles of possible relatives. The assignment consists of a computation based on these profiles to identify the victims.

The calculations and report will be graded on a scale of one to ten.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Contact information

Coordinator

• dr. E. Musta