Statistical Methods for Criminology (online)
Date:
05/09/2024
Organised by:
The University of Edinburgh
Presenter:
Dr Ben Matthews is a Lecturer in Social Statistics and Demography at the University of Stirling
Level:
Intermediate (some prior knowledge)
Contact:
Laura Marshall
Usher.communications@ed.ac.uk
Working week: Monday - Thursday
Venue: Online
Description:
Data and statistics form the basis of much political discussion about crime, provide the foundation for evidence-based research on justice interventions, and shape our understanding of possible biases in the justice system.
However, working with any social science data can be complex, and there are particular features of working with criminological data that can pose challenges for researchers.
This is an intensive one-day workshop on criminological data and how data about crime and victimization can be understood using statistical methods. The workshop is specifically designed for criminologists and social scientists, and criminological data and examples will be showcased throughout the workshop.
The workshop will introduce common types of criminological data and how this can be modelled in the generalized linear modelling framework. Participants will be introduced to common approaches to modelling criminological data sources, such as recorded crime and victimization data using count models, and how criminologically relevant quantities of interest (such as victimization inequality measures) can be simulated from fitted models. Participants will learn about issues that can arise analysing data from the criminal justice system, such as measurement error and selection bias. Finally, the workshop will discuss the ethics of working with crime data.
The emphasis will be on interpreting outputs (e.g. from data analysis software packages) and understanding results (e.g. in published papers).
The event is intended to be engaging and informative and there will be audience participation and opportunities to ask questions. This is not a practical workshop and it does not provide training in the use of data analysis software. It will however provide a strong theoretical foundation for future engagement at practical workshops that are designed to provide hands-on training in data analysis.
A high level of mathematical ability is not required, but participants should ideally have undertaken an introductory statistics and data analysis course (e.g. a semester long module as part of a Masters degree) or have attended an NCRM workshop on Statistical Modelling.
Researchers at any career stage are welcome. The workshop focuses on criminological examples, but the issues raised will be relevant for researchers across the social sciences.
Course Timings: 10:00 - 17:00
Cost:
The fee per teaching day is: • £30 per day for students registered at UK/EU University. • £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions. • £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of its cancellation of a course, including but not limited to any travel or accommodation costs. The University of Southampton’s Online Store T&Cs also continue to apply.
Website and registration:
Region:
Scotland
Keywords:
Secondary Analysis, Analysis of existing survey data, Analysis of administrative data, Quantitative Data Handling and Data Analysis, Generalized liner model (GLM), Simulation , Research Ethics, Selection bias, measurement error
Related publications and presentations:
Secondary Analysis
Analysis of existing survey data
Analysis of administrative data
Quantitative Data Handling and Data Analysis
Generalized liner model (GLM)
Simulation
Research Ethics