GVMQAES: Quantitative Analysis of Data in Environmental Science

Module code: GVMQAES

Module provider: Geography and Environmental Science; School of Archaeology, Geography and Environmental Science

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 1

Module convenor: Dr Shovonlal Roy, email: shovonlal.roy@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: No

Last updated: 20 May 2024

Overview

Module aims and purpose

Quantitative data analysis is essential for Environmental Science. These are essential practical skills that increase our understanding of natural environmental processes and the impact of human activity on the environment (e.g. pollution, land and marine resources 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 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-available remote-sensing toolboxes. 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. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Formulate a range of environmental hypotheses and identify the appropriate statistical methods to test these 
2. Use graphical tools for preliminary data analysis and visualisation 
3. Apply a range of statistical tests, demonstrating that the assumptions of each test are satisfied and interpret the outputs from statistical tests 
4. Explain the importance of sound research design and sample collection to ensure data are reliable, suitable for the statistical test required and that the limitations of different statistical techniques are understood 

Module content

The course covers essential methods needed for environmental data analysis, including:

• Data entry and basic data handling
• Measures used to describe data e.g. measures of the ‘centre’, dispersion
• Graphical displays e.g. scatterplots, boxplots, bar charts etc.
• Probability models, particularly normal distribution
• Testing for difference between two samples (e.g. t-test) and multi-factor experiments (e.g. ANOVA)
• Testing for relationships using correlation and regression
• Experimental design and sampling
• Dealing with satellite-derived environmental data

Structure

Teaching and learning methods

Teaching will be through a combination of lecture and computer practicals following the flipped classroom approach. Split between lectures and practicals 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 of data. Students will have the chance to test their understanding and gain instant feedback through submitting weekly practical reports. A multiple-choice test and a pieces of written coursework will provide an additional opportunity to put the methods learnt into practice using real environmental data. 

Study hours

At least 30 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

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

Assessments with numerical marks

• 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 three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/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.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

• In-class discussions and Q&A during the practical sessions, 
• Written formative feedback on weekly practical reports. 

Reassessment

Additional costs