MA304-6-PT-NW:
Data Visualisation
2025/26
Mathematics, Statistics and Actuarial Science (School of)
Northwest University
Spring Special
Undergraduate: Level 6
Current
Monday 12 January 2026
Friday 26 June 2026
15
13 March 2026
Requisites for this module
(none)
(none)
(none)
(none)
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BSC I26ENW Data Science and Analytics
In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module we will look at data through the eyes of a visual detective.
We will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. We will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience.
The aims of this module are:
- to create data analysts who can identify patterns and display information from data from several sources.
- to encourage statistical thinking by a series of examples of good and not-so-good visualisations
- to guide students to develop their creativity within a scientific framework.
- To highlight how visualization plays a key role in many disciplines.
By the end of the module, students will be expected to be able to:
- Summarise and understand information on text, categorical and continuous variables
- Display graphical information and complex relationships in datasets using R
- Use advanced statistical packages like ggplot2 and produce statistical reports with Rmarkdown
Indicative syllabus
Historical examples of visualization
Cognition linked to visualization including linguistics, mathematics, natural sciences, art and wider cultural topics
Data Visualization for Human Perception
What makes a good graph – What makes a bad graph
Examining variables and basic R charts
Exploring relationships, looking for structure
Advanced plots with ggplot2
Creating statistical reports with Rmarkdown
Interactive graphs
Testing data quality through graphs
Data visualization within Industry
Telling a story
For data analysis and visualisations we will use R-studio, ggplot2 and plotly packages, as well as google visualisations and interactive plotting.
Teaching in the School will be delivered using a range of face-to-face lectures, classes, and lab sessions as appropriate for each module. Modules may also include online only sessions where it is advantageous, for example for pedagogical reasons, to do so.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Xu Chen, email: xc23776@essex.ac.uk.
Dr Xu Chen
maths@essex.ac.uk
No
No
No
No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.
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