Postgraduate Module Descriptor

SOCM029: Data Visualisation

This module descriptor refers to the 2017/8 academic year.

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

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. 2^nd 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. 2^nd ed. Springer, 2005.

Tamassia, Roberto, ed. Handbook of graph drawing and visualization. CRC press, 2013.