Module SOCM029 for 2019/0
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
SOCM029: Data Visualisation
This module descriptor refers to the 2019/0 academic year.
Module Aims
The main aims of the module are:
- To understand and apply principles of data visualization
- To develop skills in capturing and managing data for visualisation
- To analyze subject relevant data sets using data visualisation techniques
- To learn to quantitatively and qualitatively evaluate existing visualizations
- To further develop skills in using the ggplot2 package for R and related packages for data visualisation.
| On successfully completing the programme you will be able to: | |
|---|---|
| Module-Specific Skills | 1. Demonstrate proficiency in the use of R for data visualisation 2. understand code in R and implement appropriate commands to perform relevant analyses 3. Understand principles of and appropriate use of data visualization to communicate data analysis. |
| Discipline-Specific Skills | 4. Develop coding skills in a way that results in high level of synergies with quantitative research skills. 5. manipulate data in R and use the appropriate analytic tools. 6. interpret output from each program and draw appropriate inference regarding the hypotheses being tested. |
| Personal and Key Skills | 7. Demonstrate understanding of computing skills 8. Demonstrate understanding of data management skills |
Module Content
Syllabus Plan
Whilst the module’s precise content and order of syllabus coverage may vary, it is envisaged that it will include the following topics:
Course Introduction, Terminology
Introduction to R. Types of data
Main principles of data visualization
Types of statistical graphics
Cleaning and preparing data for visualisations. The package dplyr.
Basic Charts and Plots, Multivariate Data Visualization
The package ggplot2: structure of plots and commands
Principles of Perception, Color, Design, and Evaluation
Text Data Visualization
Temporal Data Visualization
Geospatial Data Visualization
Network Data Visualization
Learning and Teaching
This table provides an overview of how your hours of study for this module are allocated:
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 20 | 130 | 0 |
...and this table provides a more detailed breakdown of the hours allocated to various study activities:
| Category | Hours of study time | Description |
|---|---|---|
| Lectures with lab | 20 hours in total | 10 x 2 hour lectures and labs .These lectures cover the main concepts of the course. These practical sessions cover the application of techniques |
| Independent study | 60 hours | Reading and preparing for lectures and labs (around 4-6 hours per week); |
| Independent study | 70 hours | researching and writing assessments and assignments (researching, planning and writing the course work). |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
http://r4ds.had.co.nz/data-visualisation.html
How this Module is Assessed
In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.
Formative Assessment
A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| In-class exercises | 15 minutes each x 4 | 1-8 | Peer and oral feedback |
Summative Assessment
A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
...and this table provides further details on the summative assessments for this module.
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Practical Exercise 1 using the skills/techniques developed to investigate a research problem relevant to the students chosen discipline. | 50 | 1500 words & up to 5 data figures | 1-8 | Written Feedback |
| Practical Exercise 2 using the skills/techniques developed to investigate a research problem relevant to the students chosen discipline. | 50 | 1500 words & up to 5 data figures | 1-8 | Written Feedback |
Re-assessment
Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Practical Exercise 1 | Practical Exercise 1 (1500 words & up to 5 data figures) | 1-8 | August/September reassessment period |
| Practical Exercise 2 | Practical Exercise 2 (1500 words & up to 5 data figures) | 1-8 | August/September reassessment period |
Indicative Reading List
This reading list is indicative - i.e. it provides an idea of texts that may be useful to you on this module, but it is not considered to be a confirmed or compulsory reading list for this module.
Basic reading:
Hadley Wickham, ggplo2. Elegant Graphics for Data Analysis. 2nd ed. Springer, 2015.
Winston Chang, R Graphics Cookbook. O’Reilly, 2013.
John Chambers, William Cleveland, Beat Kleiner and Paul Tukey, Graphical Methods for Data Analysis. Wadsworth, 1983.
Edward Tufte. The Visual Display of Quantitative Information. Graphics Press, 2001.
Leland Wilkinson, The Grammar of Graphics. 2nd ed. Springer, 2005.
Tamassia, Roberto, ed. Handbook of graph drawing and visualization. CRC press, 2013.
