MA304-7-AU-CO:
Exploratory Data Analysis and Data Visualisation

The details
2019/20
Mathematical Sciences
Colchester Campus
Autumn
Postgraduate: Level 7
Current
Thursday 03 October 2019
Saturday 14 December 2019
15
01 October 2019

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

(none)

Module description

In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this course we will look at data through the eyes of a numerical 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.
For data analysis and visualisations we will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.

Aims

The aim of the course will be to create data analysts that can identify patterns and display information from data of several sources. The course will encourage statistical thinking by a series of examples of good and not-so-good visualisations and will guide students to develop their creativity within a scientific framework.

Learning Outcomes

At the end of the course students will be able to:
- Summarise and understand information on categorical and continuous variables
- Explore relationships between different variables
- Display graphical information and complex relationships in datasets using R
- Use advanced statistical packages like ggplot2 and produce statistical reports with Rmarkdown
- Create interactive graphs with R shiny and googleVis

Syllabus

- 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
- Telling a story

Module aims

No information available.

Module learning outcomes

No information available.

Module information

No additional information available.

Learning and teaching methods

Weeks: 2 and 3: 1 Lecture, 1 PC lab Weeks: 4 -9: 2 pc labs Week: 10, 3 practical pc labs Week 11: 3 lectures

Bibliography

This module does not appear to have any essential texts. To see non-essential items, please refer to the module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework   Coursework 1  31/10/2019  30% 
Coursework   Coursework 2  06/12/2019  45% 
Coursework   Coursework 3  12/12/2019  25% 

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Fanlin Meng, email: fanlin.meng@essex.ac.uk.
Dr Fanlin Meng (fanlin.meng@essex.ac.uk) and Dr Andrew Harrison (harry@essex.ac.uk)
Dr Fanlin Meng (fanlin.meng@essex.ac.uk)

 

Availability
Yes
Yes
No

External examiner

No external examiner information available for this module.
Resources
Available via Moodle
Of 82 hours, 20 (24.4%) hours available to students:
62 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information
Mathematical Sciences

Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.