MA Criminology

The course provides a comprehensive introduction to the use of descriptive and inferential statistics with a focus on introducing the R programming language. The course responds to current calls from ESRC and the British Academy to improve the quantitative skills of social science graduates and fits within the Q-Step Manchester initiative.

Indicative content: (1) Introduction to the course & software; (2) Data visualisation; (3) Statistical inference; (4) Hypothesis tests; (5) Associations between categorical variables; (6) Linear regression; (7) Real-world regression; (8) Logistic regression.  

The unit aims to provide a comprehensive introduction to the use of descriptive and inferential statistics with a focus on introducing the R programming language.

On completion of the course, the student will – among other things - be able to (1) appreciate the relevance of quantitative skills for criminological research and professional development; (2) Understand basic statistical concepts; (3) use the interface and basic functions of the R programming language for data entry, formatting, filtering, and alteration; (4) develop an introductory grasp of RStudio as an interface for working with R; (5) feel confident in the use of large data sets in a computer environment.

Teaching in academic year 20/21 will reflect both University policy and local and national lockdown restrictions operating at the time of delivery. Due to the impossibility of providing socially distanced ‘over the shoulder’ support for the computer-based aspects of this unit, this course will be offered entirely online. This will include (1) media, activities and other learning material that should be engaged with before scheduled teaching; (2) a timetabled online ‘practical lab session’; (3) weekly opportunity for 1:1 support. In total, there will be the opportunity for up to 30 hours of contact.

Employability skills: In addition to subject-specific knowledge and understanding, Criminology units foster highly employable skills such as the ability to (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.

The course is assessed by means of weekly homework (60% of the overall mark) and an open book exam (40%).

Formative feedback (both individual and collective) will be given on tasks and contribution in class. Summative feedback will be given on the exam via Blackboard (Grademark).

https://jjmedinaariza.github.io/R-for-Criminologists/

Study hours: Across their course units each semester, full-time students are expected to devote a ‘working week’ of 35-40 hours to study. Accordingly each course unit demands 9-10 hours of study per week comprised of (i) timetabled contact hours, (ii) preparation, required and further reading. Part-time students study the same number of weekly hours per unit but take fewer units per sem