Concepts of Forensic Inference and Statistics

Course overview

There is an ongoing paradigm shift in evaluation of forensic evidence away from methods based on human perception and subjective judgement to methods based on relevant data, quantitative measurements, and statistical models; methods that are transparent and reproducible, use the logically correct framework for interpretation of forensic evidence (the likelihood-ratio framework), are resistant to cognitive bias, and are calibrated and validated under casework conditions. The paradigm shift is spreading across different branches of forensic science, and there is a need for more forensic practitioners and lawyers to have a working knowledge of the concepts of forensic inference and statistics. This continuing-professional-development (CPD) module will provide you with a conceptual understanding of forensic inference and statistics, including an understanding of the likelihood-ratio framework for interpretation of forensic evidence. The focus of the module is on understanding of concepts rather than practical implementation skills. No prior knowledge of statistics is assumed.

Module Learning Outcomes:

On successful completion of this module, you will:

Understand how to perform source-level forensic evaluation via quantitative implementation of the likelihood-ratio framework.
Understand how to empirically calibrate and validate forensic-evaluation systems.
Understand what cognitive bias is and be familiar with strategies for reducing its potential impact.
Be familiar with the requirements and recommendations of standards and guidelines related to evaluation of forensic evidence, and with legal admissibility of forensic evidence.

Module Content:

Logical reasoning for evaluation of forensic evidence
Concepts of statistical modelling for evaluation of forensic evidence
Empirical calibration and validation of forensic-evaluation systems
Cognitive bias in evaluation of forensic evidence
Standards and guidelines related to evaluation of forensic evidence
Legal admissibility of forensic evidence from a scientific perspective
Examples from multiple branches of forensic science

“I have hated anything maths my entire life, but this module has introduced things so steadily and sequentially (and with instant feedback and consolidation from the didactic quizzes), that I not only feel capable but have enjoyed the module."

"The organisation of materials, the repetition, and the class discussion format are great. The instructor is patient and thorough. I cannot express strongly enough that this is the best-taught class I have ever taken.”

“The lectures are always engaging and are explained well and in-depth. The pace of the lectures make it easier to keep up with the lecturer. The quizzes within the lecture slides have been a great way to make sure I have an understanding of the lecture content so far.”

Testimonials from previous students

Concepts of Forensic Inference and Statistics

How you will learn

The module is delivered entirely online. Learning resources are provided via the Blackboard Ultra virtual learning environment, and via the University’s library. You can take the module from anywhere in the world as long as you have a good internet connection. The module includes regular interactive seminars and tutorials. As necessary, seminars and tutorials will be scheduled to accommodate participants in different time zones, e.g., early morning and/or evening UK time.

The module consists of nine units of learning and two assessments of competency.

A flipped-classroom active-learning approach is adopted whereby transfer of information primarily takes place via pre-recorded lectures, other videos, and readings before class, and class time is used for interactive activities aimed at developing analytical skills and deeper understanding.

Each unit is delivered over a two-week period. For each unit, you will be provided with pre-class watching and reading and with questions and/or activities to guide your watching and reading. Each unit includes a two-hour-long seminar (in the first week) and a one-hour-long tutorial (in the second week). Seminars consist of small-group and whole-class interactive activities based on the pre-class watching and reading. During tutorials, the instructor responds to questions posed by participants.

After each seminar, you will also be provided with an online didactic quiz. An online didactic quiz presents 10 questions randomly selected from a much larger question bank, and provides immediate feedback on your answers. Each quiz can be repeated multiple times. A different set of questions will be presented each time.

Learning is cumulative and cyclical, with later parts of the module drawing on concepts covered in earlier parts of the module.

Assessment

Assessment is via two online tests that have the same format as each unit’s online didactic quiz. This is designed to encourage you to exploit the learning opportunities provided by the didactic quizzes, and in turn to exploit the learning opportunities provided by the pre-class watching and reading questions and by the in-class activities. The first test occurs in the middle of the module. The questions in the first test will assess your knowledge and understanding of the material covered in the first half of the module. The second test occurs at the end of the module. The questions in the second test will assess your knowledge and understanding of the material covered in the whole module, with a greater proportion of questions focusing on the second half of the module.

The tests are designed to assess competency. To demonstrate competency (and be awarded a pass), you must achieve a score of 80% or more by correctly answering 80 or more of the 100 questions spread across the two tests. If you do not demonstrate competency on your first attempt, you will be able to engage in additional study (and can receive support from the instructor) and will be able to reattempt one or both tests. If you achieve a raw score of 80% or more on the second attempt, you will be awarded a pass. What matters is that you achieve and demonstrate a sufficient level of competency, not how long it takes you to do so.

Key information

Credit value: 15 credits (7.5 ECTS credits)

Specific level: Master's

Mode of delivery: Online learning

Course type: Standalone module

Applications: All applications are made online using our online application form.

Start date: January 2025 , September 2025

Application deadline: We accept applications up to the first week of the month in which the module begins.

Duration and time commitment: Delivery of the module occurs during 20 weeks spread over a period of approximately 6 months. The expected study time required is the equivalent of approximately one day per week (150 hours total). Your access to all learning resources will last for 12 months. If necessary, this allows for completion of assessment of competency to occur after the first 6 months.

Meet your module director

Geoffrey Stewart Morrison
Module Director, Concepts of Forensic Inference and Statistics

The module is prepared and delivered by Dr Geoffrey Stewart Morrison. Dr Morrison is a forensic practitioner and a leading researcher in the field of forensic inference and statistics. Dr Morrison is Director of Aston University’s Forensic Data Science Laboratory, and is Chair of the British Standards Institutions’ Forensic Science Committee. He was an influential contributor to the development of ISO 21043 Forensic Science, particularly Part 4 Interpretation.

Get in touch

Entry requirements

You will need:

Undergraduate degree - pass
The module is organised to facilitate participation by individuals who already work in forensic science or law, but this is not a requirement.

International students should be outside the UK or already in the UK with a valid visa.

We are not able to accept applications from international students who wish to come to the UK solely to take this course.

English language requirements

The module is taught in English.

For applicants whose first language is not English, evidence of English-language proficiency is not required, but applicants should have sufficient English-language proficiency to understand readings and lectures, and to actively participate in discussions.

The online application form is a generic form covering all programmes at Aston University. Much of the information requested is not needed for applications for this CPD module, and, even if it is submitted, will not be used.

In order to minimise your work on the application process, please follow the advice below:

Initial
Register an account on the application portal and log in.
On the menu bar, select “My Applications” > “Submit Application”, or scroll down and select “Apply to Aston”.

Application Details
Complete: Course details (select Concepts of Forensic Inference and Statistics)
Complete: Aston graduate details
Skip: Agent details
Mark the section complete.

Qualifications
Add an undergraduate degree (or higher), including uploading a copy of your degree certificate or transcript.
Do not add any additional qualifications.
Complete: English language
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English Language Requirements
This section appears if you indicated that English was not your first language.
Do not upload any English language qualification documents.
Answer the questions.
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Work History
Skip all questions.
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Personal Statement
Write one-sentence answers to the following questions:

Do you work in forensic science, or are you studying forensic science?
What branch of forensic science do you work in or plan to work in?
Do you work as a lawyer, or are you studying law?
Where will you usually be taking the module from (e.g., city, state, country)?

Do not write anything else.
Your answers to these questions will help us with planning. They will not affect admission.
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Visa
Indicate that you do not require a visa.
International students must be outside the UK or already in the UK with a valid visa. We are not able to accept applications from international students who wish to come to the UK solely to take this CPD module.
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References
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Funding
Indicate source of finding.
Your answer will not affect admission.
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Submission
Review the application and submit.