- UCAS course code
- UCAS institution code
BASS Social Anthropology and Data Analytics
Year of entry: 2023
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Course unit details:
Making Sense of Criminological Data
|Unit level||Level 2|
|Teaching period(s)||Semester 1|
|Offered by||School of Social Sciences|
|Available as a free choice unit?||Yes|
Data – including crime data - is everywhere today and affects all aspects of everyday life. This being the case, it is important that we possess the ability to make sense of these data, and to use them to draw meaningful conclusions about the world around us. This course is designed to get you working with real-world data related to crime and criminal justice, and gives you new skills and confidence in manipulating, visualising and interpreting it.
Indicative content: (1) Data sets & variables; (2) Describing & visualising single variables; (3) Making comparisons – the basics; (4) Concepts, operationalisation, measurement; (5) Making comparison – research design; (6) Data visualisation; (7) Looking at trends (8) Qualitative methods 1; (9) Qualitative methods 2; (10) Course review & project support.
The unit aims to (1) introduce students to quantitative and qualitative sources of information on issues of relevance to criminology, social policy, and other social science disciplines; (2) introduce students to the principles underlying statistical and qualitative analysis; (3) develop students’ basic skills in producing, interpreting, writing up, and visualising the results of data analysis; (4) equip students with basic skills using software for data analysis ; (5) provide students with the skills necessary to critically evaluate both academic and media accounts of statistical and qualitative research.
On completion of the course, the student will be able to (1) identify some key data sources in criminology and other areas of social policy; (2) demonstrate a critical awareness of key data quality issues and how they are linked to research design decisions; (3) produce, read, and interpret quantitative information in the form of tables and graphs; (4) understand basic exploratory data analysis and principles of good data visualisation; (5) understand the different levels at which social and personal characteristics (variables) are measures and how resulting data are distributed; (6) Become aware of the range of existing qualitative data and basic approaches to their analysis.
Teaching and learning methods
Teaching methods will be flexible and allow us to adapt to changing conditions, however, the common intention across units is to provide a blended offer of the best in online and on-campus teaching that includes: (1) whole-class computer labs used for a range of exercises and activities; (2) high quality online learning materials; (3) a weekly discussion/feedback session; (4) 1:1 support via a subject-specific contact hour.
- (i) analyse, critique and (re-)formulate a problem or issue; (ii) rapidly and thoroughly review/rate argument and evidence from targeted bibliographic searches; (iii) plan, structure and present arguments in a variety of written formats and to a strict word limit, (iv) express ideas verbally and organise work effectively in small teams for a variety of written and oral tasks; (v) obtain, manipulate and (re-)present different forms of data; (vi) manage time effectively; (vii) reflect on and improve performance through feedback.
|Written assignment (inc essay)||80%|
The course is assessed by means of weekly homework submissions (20%) and a 2500-word project report (worth 80%) .
Formative feedback (both individual and collective) will be given on tasks and contribution in class. Summative feedback will be given on both assessed components via Blackboard (Grademark).
Blastland, Michael, and Andrew W. Dilnot (2008) The tiger that isn’t: seeing through a world of numbers. London: Profile books.
|Scheduled activity hours|
|Practical classes & workshops||20|
|Independent study hours|
|Nico Trajtenberg||Unit coordinator|
|David Buil Gil||Unit coordinator|
Across their course units each semester, full-time students are expected to devote a ‘working week’ of around 30-35 hours to study. Accordingly each course unit demands around 10-11 hours of study per week consisting of (i) 3 timetabled teacher-led hours, (ii) 7-8 independent study hours devoted to preparation, required and further reading, and note taking.
Restricted to: BA (Criminology) students for which this subject is compulsory, also available to students across the Faculty of Humanities depending on the availability of places. Students in the criminology pathways of BASS will be given priority.
This course is available to incoming study abroad students university wide.
Pre-requisites: We assume in our teaching that students have previously taken a course on research methods covering basic principles of data collection and research design. Although the course focuses on criminological data the techniques and ideas covered here can be used in other social science contexts. No criminological knowledge is required for taking this course unit.
See Law School timetable