Module Details
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title KEY SKILLS FOR ENVIRONMENTAL DATA ANALYSIS
Code ENVS202
Coordinator Prof CW Hughes
Earth, Ocean and Ecological Sciences
C.W.Hughes@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2018-19 Level 5 FHEQ First Semester 15

Aims

To develop skills in environmental data analysis by applying the Matlab computing package to process, analyse and plot data.

To develop a critical approach to the results of data analysis.

Learning Outcomes

1. Knowledge and Understanding
 

At the end of the module the student should

a) know how to write a program script in Matlab

b) know how to process and plot ocean and climate data using Matlab

2. Intellectual Abilities
 

At the end of the module the student should be able to:

a) know how to construct problems and use problem solving skills.

b) analyse and interpret signals in environmental data.

c) implement programming methods used for simple models and time-series analysis

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3. Subject Based Practical Skills
 

At the end of the module the student should be able to:

a) write a computer program to analyse and plot environmental data

b) interpret a range of forms of plotted data 
4. General Transferable Skills
 

At the end of the module, the student should have:

a) Gained ability in formulating problems and acquiring order of magnitude solutions

b) Gained computing skills and familiarity with computing methods and programming

c) Gained confidence and ability in interpreting data presented in a variety of forms

Syllabus
1  Syllabus

Semester 1 ( exact timings may vary)

Rationale (week 1)

•                Introduction to the course, benefits from using Matlab to solve climate, ocean and ecological problems involving large data sets, ways of presenting data.

 

Block 1 Computing skills using Matlab (weeks 2-5)

•                An Introduction to the computing package Matlab

•                Matlab programming (use of scripts, flow control)

•                Matlab input and output of data

•                Matlab plotting of data

•                Wr iting scripts and using Matlab functions: fitting a straight line (regression) to data and correlation

•                Use of "if" conditional statements to test data

•                Use of loops to analyse arrays of data

•                Simple models: finite differencing to predict the future


Block 2 An application to Climate data (weeks 6-7)

•                Analysis of atmospheric carbon dioxide record for the last 50 years and calculate the implied heating over last 50 years and

•                Evaluate changes in ocean acidity and partitioning of carbon be tween the atmosphere and ocean.


Block 3 Using real-world data to develop programming skills in Matlab (weeks 8-11)

•                Simple contouring of data

•                Reading, plotting and interpreting a large dataset

•                Introduction to more advanced techniques (animation, EOFs and their interpretatio n).




   


Teaching and Learning Strategies

Lecture - Introduction of the week''s programming technique and the associated data problem.

Laboratory Work - Computer laboratory to develop the programming technique and apply it to real data.

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 10
Introduction of the week's programming technique and the associated data problem.
    30
Computer laboratory to develop the programming technique and apply it to real data.
    40
Timetable (if known)              
Private Study 110
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
             
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Coursework  Test length approxim  Semester 1, set in about week   30  Yes  Standard UoL penalty applies  VITAL Online test 1: Matlab techniques and data interpretation 
Coursework  Test length approxim  Semester 1, set in about week   15  Yes  Standard UoL penalty applies  VITAL online test: Matlab techniques and global Carbon part 1. 
Coursework  Test length approxim  Semester 1, set in about week   15  Yes  Standard UoL penalty applies  VITAL online test: Matlab techniques and global Carbon part 2. 
Coursework  Test length approxim  Semester 1, set in week 10, de  40  Yes  Standard UoL penalty applies  VITAL online test: Matlab techniques and data interpretation 2. Notes (applying to all assessments) - none 

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.
Explanation of Reading List: