GVMQAD-Quantitative Analysis of Environmental Data

Module Provider: Geography and Environmental Science
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2020/1

Email: shovonlal.roy@reading.ac.uk

Type of module:

Summary module description:
Quantitative data analysis is essential for Environmental Science. These practical skills increase our understanding of natural environmental processes and the impact of human activity on the environment (e.g. pollution and land management) through the analysis of data collected during practical investigations. This module will provide an overview of commonly used statistical and graphical techniques for environmental data analysis. Students will have the opportunity to design simple experiments, collect and analyse their own data, as well as analyse real data sets provided from different environmental research studies.

Aims:

To learn how to analyse environmental data by applying and interpreting the outputs from a range of classic and modern statistical methods using Minitab and freely-avaialble remote-sensing toolboxes.

Assessable learning outcomes:

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

• Formulate a range of hypotheses and identify the appropriate statistical methods to test these


• Use graphical tools for preliminary data analysis


• Apply a range of statistical tests, demonstrating that the assumptions of each test are satisfied


• Interpret the outputs from statistical tests


• Explain the importance of sound research design and sample collection to ensure data are reliable and suitable for the statistical test required

Additional outcomes:

The course will develop general computing skills, particularly the use of Excel, Minitab and remote-sensing toolboxes.

Outline content:

Content covered includes:

• Data entry and basic data handling


• Descriptive statistics


• Graphs


• Tests for differences between two groups (e.g. t-test)


• Tests for differences between more than two groups (ANOVA)


• Regression


• Experimental Design


• Sampling


• Remote-sensing images

Brief description of teaching and learning methods:

Teaching will be through a combination of lecture (8x2 hours) and computer practicals (8x2Ìýhours including break). Split between lectures andÌýpracticals will vary between weeks depending on the topic. Total contact hours will be 3-4 hours per week. Methods will be introduced and discussed in lectures and practiced during practicals where students will collect and analyse various types ofÌýdata. Students will have the chance to test their understanding and gain instant feedback t hrough submitting weekly practical reports andÌýmultiple choice tests in class. A single piece of coursework will provide an additional opportunity to put the methods learnt into practice using real environmental data.

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

25000 word (max) report on acquiring and analysing environmental data from advanced satellite remote-sensing

Formative assessment methods:

Weekly practical reports and formative feedback.

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Assessment requirements for a pass:
An overall mark of 50%

Reassessment arrangements:
Resubmission of the report in August

Additional Costs (specified where applicable):

1. Required text books:


2. Specialist equipment or materials:


3. Specialist clothing, footwear or headgear:


4. Printing and binding:


5. Computers and devices with a particular specification:


6. Travel, accommodation and subsistence:

Last updated: 4 May 2020