MA Criminology

Year of entry: 2022

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Course unit details:
Data Analysis with R & RStudio

Course unit fact file
Unit code CRIM70821
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Criminology
Available as a free choice unit? Yes

Overview

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.  

 

Aims

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.

Learning outcomes

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 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) a workshop used for a range of discursive exercises; (2) high quality learning materials; (3) 1:1 support via a subject-specific contact hour

Transferable skills and personal qualities

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.

Employability skills

Analytical skills
Criminology units foster highly employable skills such as the ability to (i) analyse, critique and (re-)formulate a problem (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.
Oral communication
Problem solving
Written communication

Assessment methods

Method Weight
Other 60%
Written exam 40%

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

Feedback methods

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).

Recommended reading

Study hours

Scheduled activity hours
Practical classes & workshops 16
Independent study hours
Independent study 50

Teaching staff

Staff member Role
Tomás Diviák Unit coordinator

Additional notes

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.

 

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