Course manual 2019/2020

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.

This Course has two main topics:

The biology and genetics of DNA-evidence, as well as the current methods for the analysis and interpretation of DNA traces:
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

• Fundamentals of Forensic DNA Typing, J.M. Butler, Elsevier, 2010
• Statistics and the Evaluation of Evidence for Forensic Scientists, C. Aitken and F. Taroni, Wiley, 2004.

Syllabus

Lecture notes and power point presentations

Software

Hugin
LRmix

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. apply the Bayesian paradigm for Forensic Statistics to DNA-evidence, i.e. to compute match probabilities for standard DNA profiles and, for example, mixtures, relatedness issues and database search,
3. apply some relevant basic statistical procedures to test the validity of DNA-matching procedures and models
4. create Bayesian networks to address e.g. activity-level questions or a combination of evidence
5. Apply a relevant statistical analysis in problems of Kinship, relatedness in pedigrees, DVI and Familial searching
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

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

Activity	Hours
Hoorcollege	40
Presentatie	4
Tentamen	3
Self study	121
Total	168	(6 EC x 28 uur)

Assessment

Item and weight	Details
Final grade
50% Tentamen	Must be ≥ 5.5, Mandatory
10% Bayesian Framework exercise hand in	Must be ≥ 5.5, Mandatory
15% Bayesian network	Must be ≥ 5.5, Mandatory
10% Group Presentations Biological Topics	Must be ≥ 5.5, Mandatory
15% DVI Assignment	Must be ≥ 5.5, Mandatory

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. When a student has not fulfilled this requirement, the examiner will register the mark ‘did not fulfil all requirements’ (NAV) whether or not the averaged grade is sufficient.

The components will be weighted as follows:

Hand in exercise Baysesian Framework (10%).
Group assignment on Bayesian networks (15%).
Group assignment mixture analysis (0%; not graded).
Group presentations on biological topics (identification and presumptive testing )(10%).
Individual DVI assignment, to hand in at the final exam (15%)

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 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. Both count for half of the score for the exam.

The final grade will be announced at the latest on 15 th of April (= 15 working days after the final course activity). Between the 15th of April to May 13th (= 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			x
2	1, 3, 6	x			x
3	6	x			x			x
4	2	x			x			x
5	5, 6	x			x			x
6	2, 6					x		x
7	7	x						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 (see https://studiegids.uva.nl/xmlpages/page/2019-2020/zoek-opleiding/opleiding/5670).

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 Hand in exercise Bayesian Framework

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 the identification and presumptive testing of tissular origin if human biological traces. 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

Course structure

Weeknummer	Onderwerpen	Studiestof
1
2
3
4
5
6
7
8

Timetable

The schedule for this course is published on DataNose.

Last year's course evaluation

In order to provide students some insight how we use the feedback of student evaluations to enhance the quality of education, we decided to include the table below in all course guides.

Forensic Statistics and DNA evidence (6EC)	N=34
Strengths The combination between statistics on one hand and DNA on the other was appreciated. The course gives a good insight how to apply learned knowledge to the practical field. The practicals and assignments were very useful, especially the Island Problem and DVI assignments were very much appreciated.	Notes for improvement The course seemed unorganized due to a lack of communication between the teachers. The workload of the body fluid presentation was unbalanced which was evaluated as unfair: Some groups spent 8 hours on an assignments where others spent only 1 hour. The exam seemed a bit unbalanced in terms of the DNA en statistics part. The Bayesian network assignment was, in contrast to the other assignments, very hard to understand. The purpose of the assignment as well as the learning outcomes were not clear.
Response lecturer: The coordination between lectures must be optimized. It’s advised to have a maximum of 2 or 3 teachers (incl. guest lecturers) and it’s important to organize the structure before the start of the course. The teacher coordinator(s) must be present at or at least aware of (the content of) the guest lectures. It’s also advised to organize the Canvas page on date instead of the name of the teachers. The teacher should look into the workload of the assignments and equalize this for all the groups. To balance the workload by either a heavy one in the first term and an easier one in the last (and vice versa) between groups could be an alternative. For the exam, it’s was already advised to start with the statistics part, this should stay the same. It might be an option to make the exam shorter. The purpose of the Bayesian network assignment must be specified beforehand and it must be clarified how Bayesian network can be used in a practical manner. Guidance and feedback in this assignment should be optimized. In the academic year 2019-2020 there will be a new teachers team due to retirement of two teachers. With the new team the overall structure and set up of the course will be reviewed with the aim to strengthen the coherence of the course, the workload and purpose of the assignments.

Contact information

Coordinator

dr. Maarten Blom

Owner	Master Forensic Science
Coordinator	dr. Maarten Blom
Part of	Master Forensic Science, year 1

Forensic Statistics and DNA-evidence