The University of Southampton
Courses

ENVS2011 Advanced Quantitative Methods

Module Overview

We are now in the era of “big data”. In the environmental context, this results in large, usually complex datasets which have the potential to shed light on the challenges faced by environmental managers. Statistical modelling provides a useful tool to be able to explore the stories that these datasets can tell. This module will cover the theory of statistical modelling, as well as teaching you how to handle complex environmental datasets efficiently in order to visualise, explore and model the underlying processes.

Aims and Objectives

Module Aims

This module aims to build upon the skills learnt in ENVS1005 to enable you to visualise, explore and build predictive statistical models from large and complex datasets.

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • The need for both a multi-disciplinary and an interdisciplinary approach in advancing knowledge and understanding of Earth systems, drawing, as appropriate, from the natural and the social sciences
  • The processes which shape the natural world at different temporal and spatial scales and their influence on and by human activities
  • The terminology, nomenclature and classification systems used in environmental science
  • Methods of acquiring, interpreting and analysing environmental science information with a critical understanding of the appropriate contexts for their use
  • The contribution of environmental science to the development of knowledge of the world we live in
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Analysing, synthesising and summarising information critically, including prior research
  • Collecting and integrating several lines of evidence to formulate and test hypotheses
  • Applying knowledge and understanding to complex and multidimensional problems in familiar and unfamiliar contexts
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Receiving and responding to a variety of information sources (eg textual, numerical, verbal, graphical)
  • Communicating appropriately to a variety of audiences in written, verbal and graphical forms
  • Appreciating issues of sample selection, accuracy, precision and uncertainty during collection, recording and analysis of data in the field and laboratory
  • Preparing, processing, interpreting and presenting data, using appropriate qualitative and quantitative techniques and packages including geographic information systems
  • Solving numerical problems using computer and non-computer-based techniques
  • Using the internet critically as a means of communication and a source of information
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • Planning, conducting, and reporting on environmental investigations, including the use of secondary data
  • Referencing work in an appropriate manner

Syllabus

This module will cover, but is not limited to: - Data visualisation techniques - Time-series analysis and predictive techniques - Multivariate regression techniques - Non-linear regression techniques - Ordination methods - Cluster analysis - Bayesian techniques

Special Features

For students with specials needs, an individual assessment with be made and appropriate arrangements made to ensure they are enabled to benefit from the exercise or an equivalent experience.

Learning and Teaching

Teaching and learning methods

The module consists of a series of lectures and workshops covering the theory, background and potential applications of the modelling techniques covered. These are supplemented by practical computer sessions which enable you to put the theory into practice.

TypeHours
Follow-up work33
Revision30
Preparation for scheduled sessions18
Wider reading or practice25
Lecture11
Practical classes and workshops33
Total study time150

Assessment

Assessment Strategy

.

Summative

MethodPercentage contribution
Class Exercise  (120 minutes) 50%
Class Exercise  (120 minutes) 50%

Referral

MethodPercentage contribution
Test  (120 minutes) 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisite module/s: ENVS1005 Quantitative Methods

Pre-requisites

To study this module, you will need to have studied the following module(s):

CodeModule
ENVS1005Quantitative Methods

Costs

Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Travel Costs for placements

The costs for field visits are covered within programme costs; there are no additional costs for the student. Requirements for suitable clothing and footwear are specified in the Risk Assessment for field visits; students are expected to provide these themselves. There are no cost implications for students.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.

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