Course manual 2019/2020

Course content

An important goal of the course is to provide students with the required knowledge of statistical and probabilistic reasoning to distinguish correct from erroneous argumentation when applied to Forensic Science. Intuitive reasoning is frequently the source of serious misconceptions that all too often have lead to wrong juridical sentences. In the course, the students will see how to recognize and avoid such mistakes through formalistic analysis.

A second goal is to provide students with a basic toolbox for statistical estimation and hypothesis testing. The course is not meant as an advanced statistics course, but we will spend considerable effort on understanding and applying statistical tests such as the standard normal test, the student-t test and – ultimately - the chi-square test.

Study materials

Literature

Schneps and C. Colmez. Math on Trial. Ingram Publishers Services US, 2013.

Aitken and Taroni. Statistics and the Evaluation of Evidence for Forensic Scientists. John Wiley And Sons Ltd., Second edition, 2004.

Other

Introduction to Statistics - Online Edition. David M. Lane (ed.). With contributions by David Scott, Mikki Hebl, Rudy Guerra, Dan Osherson, and Heidi Zimmer

Essential Mathematics and Statistics for Forensic Science. Craig Adam. Wiley, 2010.

Objectives

1. use the basic concepts relevant for statistical and probabilistic analysis and hypothesis testing
2. apply basic statistical and probabilistic methods and techniques to stylized forensic case formulations (probability, discrete and continuous distributions, hypothesis testing)
3. evaluate the risks (i.e. possibilities of drawing wrong conclusions) and detect erroneous use of probabilistic and statistical methods and techniques when applied to e.g. data sets, excerpts of criminal trials and scientific articles
4. deliver a critical analysis of the use of statistical tools in the forensic context in a clear, coherent and understandable way

Teaching methods

Lecture
Presentation/symposium
Self-study
Working independently on e.g. a project or thesis

Prior to the first lecture the course starts with an individual preparation/refresher about statistical concepts (mean, median, mode, variance, covariance, correlation, regression) and probabilistic fundamentals (probability space, axioms of probability, basic combinatorics, conditional probability).

In weeks 37-41 the theory classes with accompanying exercise classes will provide students with the required theoretical knowledge for use in Forensic Science. There are also weekly exercise classes where specifically assigned problems will be solved and weekly question hours where more theoretical issues can be discussed.

In week 39 there will be a midterm test about the material covered so far.

In the second part of the course, the emphasis will be on the use of statistical estimation and hypothesis testing, using the same format of theory, exercise and question hour classes.

In parallel, the students will work in small teams on an assignment to critically analyze a number of criminal trials (each group is assigned a Chapter from the book Math on trial). The cases serve as an illustration of the impact erroneous reasoning may have on the course of justice. The focus in the assignments is to identify the correctness in using statistical and probabilistic analysis and techniques in the forensic practice. The different cases will give the student insight into a wide range of applications as well as a broad spectrum of erroneous reasoning in forensic applications, e.g., alleged murder, DNA analysis, database trawling and handwriting comparisons.

In week 42, the groups will present their work in a full-day meeting. The exam is in week 43.

Learning activities

Activity	Hours
Excursie	8
Hoorcollege	10
Presentatie	16
Tentamen	3
Vragenuur	12
Werkcollege	18
Self study	73
Total	140	(5 EC x 28 uur)

Assessment

Item and weight	Details
Final grade
15% Midterm test	Must be ≥ 5.5, Mandatory
35% Math on Trial assignment	Must be ≥ 5.5, Mandatory
50% Resit final exam	Must be ≥ 5.5, Mandatory

The components will be weighted as follows:

Midterm test (15%)
Math on Trial assignment (individual grade, 35%)
Final exam (50%)

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 fulfil all requirements’ (NAV) whether or not the averaged grade is sufficient.

The final grade will be announced at the latest 15 working days after the final course activity. Between this date and 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 (see Appendix 1)
Learning outcomes	Components (see above)	1	2	3	4	5	6	7	8	9	10
1	1, 3		x			x
2	2, 3				x	x
3	2, 3							x	x
4	2				x		x			x

Table 1: Table of specification: the relation between the learning outcomes of the course (see 1.3), the assessment components of the course (see 2.4) and the Exit Qualifications (EQ) of the Master’s Forensic Science (described in the Introduction in the Course Catalogue)

Assignments

1 Midterm test

The material of the first two theory classes and accompanying exercise classes will specifically be examined in the (individual) written midterm test in week 39.

2 Group assignment: Math on Trial

To illustrate the danger in wrongly using statistical and probabilistic reasoning, all students will study a chapter of the book Math on Trial (in groups) and prepare a joint presentation about (i) the contents of this chapter, as well as (ii) their analysis of it. Two (or three) students from the group will present their results in class. The audience is formed by students from other groups who should engage in a critical debate through questions to the presenting group.

The slide book and the presentation will be graded (one grade for the group). The individual grade of each student can deviate up to one grade point from the group’s grade, depending on their individual participation in discussions about their own presentation and that of other groups. The student’s individual grade for the assignment must not be lower than 5.5 in order to pass the course and will contribute to the final grade (see Section 2.4 for details).

3 The final examination

The material of the four theory classes and accompanying exercise classes will specifically be examined in the (individual) final written exam. The result of the exam must not be lower than 5.5 in order to pass the course (see Section 2.4 for details).

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.

Statistics for Forensic Science (5EC)	N 42
Strengths The course was much better evaluated compared to last year. Separating Professional Development from Statistics for Forensic Science has been a good idea. Teacher was highly appreciated. He listened carefully to the questions of the students and explained everything very well. The students liked the way the course was structured every week.	Notes for improvement The alignment between the teachers Bas and Sindo: Bas often did not know which exercises were made previously for instance. The students mentioned that the book ‘Statistics and the Evaluation of Evidence for Forensic Scientists’ (by Aitken and Taroni) was not helpful during the course and the exam. The students found the end-of-term exam very difficult and this was mainly due to the easy questions on the midterm exam. As a result, the students expected the questions on the end-of-term exam to be much easier/clearer.
Response lecturer: The course has a much better evaluation compared to last year. The teachers had a very clear division of tasks and on purpose the lecturer teacher did not explain exercises to students as to not confuse students with a different explanation from the tutorial teacher. We will emphasize this to the students next year, so they know what to expect. The mid-term exam was previously part of the end-of-term exam. It covers the first two weeks and is therefore easier study material then the end-of-term exam. This will be emphasized towards the students next year. If students do the practice exams, they should be aware of the level of the end-of-term exam. The book was used for the first time this year. The teachers will better integrate the book in the course and in the exam. We will keep the open book exam and during the course provide more guidance on how to use the book for the exam. Next year, we will ask students to prepare the study material of the first week themselves and they will do an obligatory pre-test (pass/no-pass) to check whether they have understood. The teachers expect that part of the students will not have the required level for statistics and in this way students are aware they need to work on it.

Contact information

Coordinator

prof. dr. R. Nunez Queija

Owner	Master Forensic Science
Coordinator	prof. dr. R. Nunez Queija
Part of	Master Forensic Science, year 1

Statistics for Forensic Science