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 and learning across course units consists of: (1) preparatory work to be completed prior to teaching sessions, including readings, pre-recorded subject material and online activities; (2) a weekly whole-class lecture or workshop; (3) a tutorial; and (4) one-to-one support via subject specific office hours.

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.

Weekly Homework Tasks & Quizzes: 40% 
Final Comprehensive Assessment: 60% 
 

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 consisting of (i) teacher lead activities and sessions, (ii) preparation, required and further reading.

Part-time students study the same number of weekly hours per unit but take fewer units per semester.