Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title An Introduction to Data Visualization Using R
Code SOCI523
Coordinator Dr P Campbell
Sociology, Social Policy and Criminology
Year CATS Level Semester CATS Value
Session 2023-24 Level 7 FHEQ Second Semester 10


This module aims to
• Introduce students to R, RStudio and the ‘tidyverse’
• Explain the main principles which can be used to visualize data
• Enable students to implement these principles programmatically
• Encourage reflection on the role that visualization plays in society

Learning Outcomes

(LO1) Demonstrate the ability to design appropriate visualizations of numerical data

(LO2) Write appropriate code to implement their designs

(LO3) Integrate their designs into written reports

(LO4) Understand, critique, and suggest improvements for visualizations in the public domain

(S1) Communication (oral, written and visual) - Following instructions/protocols/procedures

(S2) Communication (oral, written and visual) - Communicating for audience

(S3) Skills in using technology – Using R

(S4) Numeracy/computational skills - Confidence/competence in measuring and using numbers

(S5) Critical thinking and problem solving - Evaluation



Topics covered will include:

Introduction to Data Visualization
Working in R and RStudio
Using RMarkdown
Objects and repetition
The ‘grammar of graphics’
‘Tidy’ data
Critiquing existing visualization
The use of colour and shape
Grouping and comparison
Applying themes and customising visualization
Integrating image and text

Teaching and Learning Strategies

Teaching Method 1: Workshop

Scheduled Directed Student Hours: 20

Unscheduled Directed Student Hours:

Description: 2 hour workshop sessions will be held weekly for 10 weeks consisting of two parts: troubleshooting problems with practical tasks which the students have attempted before class, and practicing the development of new skills within class.

Attendance Recorded: Yes

Self-Directed Learning Hours: 80

Description: Asynchronous ‘e-lecture’ and training materials will be available weekly which the students will engage with outside of the workshop sessions. In addition, students will need to engage independently with a range of readings and practical exercises to prepare for workshop sessions.

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours           18

Timetable (if known)              
Private Study 80


EXAM Duration Timing
% of
Penalty for late
CONTINUOUS Duration Timing
% of
Penalty for late
Assessment 1 Assessment Title: RMarkdown Report Assessment Type: Coursework Duration / Size: ~3,000 words Weighting: 100% Reassessment Opportunity: Yes Penalty for Late Submissio    100       

Recommended Texts

Reading lists are managed at Click here to access the reading lists for this module.