The University of Southampton
Courses

ENVS6034 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 that have the potential to shed light on the challenges faced by environmental managers. Statistical modelling provides a useful tool set for exploring and uncovering the stories that these datasets can tell. This module will cover the background to 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 earlier statistics courses 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 terminology, nomenclature and classification systems used in environmental science.
  • the processes which shape the natural world at different temporal and spatial scales and their influence on and by human activities
  • the contribution of environmental science to the development of knowledge of the world we live in,
  • methods of acquiring, interpreting and analysing environmental science information with a critical understanding of the appropriate contexts for their use
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • 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.
  • communicating appropriately to a variety of audiences in written, verbal and graphical forms.
  • using the internet critically as a means of communication and a source of information.
  • receiving and responding to a variety of information sources (eg textual, numerical, verbal, graphical).
  • appreciating issues of sample selection, accuracy, precision and uncertainty during collection, recording and analysis of data in the field and laboratory.
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.
  • collecting, recording and analysing data using appropriate techniques in the field and laboratory.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • 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
  • analysing, synthesising and summarising information critically, including prior research.
  • recognising and using subject-specific theories, paradigms, concepts and principles.

Syllabus

This module will include, but is not limited to: o Data preparation and visualisation techniques o Time-series analysis and forecasting techniques o Multivariate analyses o Non-linear regression techniques o Ordination methods o Cluster analysis o Bayesian techniques The focus will be on combining the strengths of Excel, SPSS and R, plus other open-source packages such as AM Statistical Software and JASP.

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 will be supplemented by practical computer sessions that enable you to put the theory into practice.

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

Assessment

Assessment Strategy

Referral method - In class test, 2 hours. This summative assessment must be passed in order to complete the module.

Summative

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

Referral

MethodPercentage contribution
Class Test  (120 minutes) 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisite module/s: ENVS1005 Quantitative Methods for 3906 MEnvSci Aquatic Env&Resources, 3907 MEnvSci Biodiversity & Cons, 3908 MEnvSci Env Change, 3909 MEnvSci Sustainable Env Mang

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:

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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