GV1DEN-Data Environment

Module Provider: Geography and Environmental Science
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Autumn / Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3

Module Convenor: Prof Andrew Wade
Email: a.j.wade@reading.ac.uk

Type of module:

Summary module description:

This module will introduce numerical concepts and techniques required to process and analyse environmental data improving or consolidating numerical skills required for studying environmental science. It will train students in using the selected data management, processing and statistical packages, and data visualisation. Data will be drawn from other thematic modules taught at Part 1 and will assist students with managing numerical and data processing tasks set in other modules. The module will consist of lectures and practical sessions with a strong emphasis on practical learning. Assessment will be via two online tests and a project related to processing, analysis and visualisation of environmental data. 

Aims:

This module aims to help students to consolidate and advance numerical skills which will help them to progress through the programme. Specifically, it aims to consolidate students’ skills in algebra, acquire and advance skills in basic mathematics and statistics, numerical data management and visualisation, and the use of selected data processing and statistical packages.

Assessable learning outcomes:

By the end of this module, students should be able to: 

• Perform basic calculations and read, re-arrange and solve algebraic equations 


• Understand the basics of calculus


• Analyse data using a range of common statistical techniques 


• Present data in graphical format


• Manage, analyse and visualise data using common software packages

Additional outcomes:

This module will provide the opportunity to develop the following transferable skills:

• Teamwork


• Data handling


• Data presentation


• Written presentation

Outline content:

Lecture content

• Basic maths skills 


• Algebraic manipulations 


• Descriptive statistics


• Parametric and non-parametric statistics


• Univariate and multivariate analyses 


• Goodness-of-fit indices


• Comparison of samples


• Introduction to calculus


• Introduction to data management and visualisation

Practical content

• Data management 


• Data presentation and visualisation using selected software packages


• Statistical analysis using selected software packages (e.g. Excel, R)


• Introduction to scientific programming (e.g. R)

Brief description of teaching and learning methods:

This module will be delivered through interactive lectures and practical classes.

Contact hours:

	Autumn	Spring	Summer
Lectures	10	5
Project Supervision		15
Practicals classes and workshops	20	10
Guided independent study:
Wider reading (independent)	10	5
Wider reading (directed)	10	5
Exam revision/preparation	20	15
Preparation for seminars	30	15
Preparation of practical report		10
Group study tasks		20
Total hours by term	100	100	0
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Report	70
Class test administered by School	30

Summative assessment- Examinations:

N/A

Summative assessment- Coursework and in-class tests:

The problem solving tests will allow you to demonstrate your understanding of the fundamental mathematical and statistical concepts and techniques. Each test will complete a thematic block and will be taken before moving to the next topic. This step-by-step assessment is designed to consolidate knowledge, receive timely feedback and feed-forward and minimise risk of failure. 

The written report, accompanied by graphical presentation of environmental data, will complete projects undertaken by the students and supervised by the members of the teaching team. These projects will be related to real environmental issues and data giving students hands-on experience of analysing environmental data early in their course and enabling students to demonstrate their ability to interpret and present environmental data.

Formative assessment methods:

Assessment and feedback during the practical sessions.

Penalties for late submission:

The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

A mark of 40% overall.

Reassessment arrangements:

Resubmission of written report.

Additional Costs (specified where applicable):

1. Required text books: None


2. Specialist equipment or materials: None


3. Specialist clothing, footwear or headgear: None


4. Printing and binding: None


5. Computers and devices with a particular specification: None


6. Travel, accommodation and subsistence: None

Last updated: 22 September 2022