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 Professor CW Hughes
Earth, Ocean and Ecological Sciences
C.W.Hughes@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2022-23 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

(LO1) Use the MATLAB interface to create scripts and functions

(LO2) Understand the building blocks of programming: variable assignment, conditional statements, program flow control, and function calls.

(LO3) Be able to read, plot, and interpret a variety of data types.

(LO4) Be able to construct a program to read data, perform calculations on it, and plot the results, using function calls where appropriate.

(S1) Problem solving skills

(S2) Numeracy

(S3) IT Skills

(S4) Data intepretation

Syllabus
 

Syllabus Semester One (exact timings may vary)

Rationale Week One

Introduction to the course, benefits from using MATLAB to solve climate,ocean and ecological problems involving large data sets.  Setting up MATLAB and getting started .

Block One Computing skills using MATLAB

An Introduction to the computing package Matlab
Matlab programming (use of scripts, flow control)
Matlab input and output of data
Matlab plotting of data  
A sea level example.

Block Two Using real-world data to develop programming skills in MATLAB.
Reading, plotting, and calculating derived information from an atmospheric CO2 dataset.

Block Three An application to Climate data
Use of "if" conditional statements to test data
Use of loops to analyse arrays of data
Simple contouring of data
Controlling MATLAB functions and exploring further.
Least squares fitting, correlations, and variance explained.

Teaching and Learning Strategies

Teaching Method 1 - Lecture
Description: Introduction of the week's programming technique and the associated data problem.
Asynchronous, online.

Teaching Method 2 - Laboratory Work
Description: Computer laboratory to develop the programming technique and apply it to real data. This is a 2 hour session with the lecturer present as a demonstrator to help. Students are encouraged to discuss problems and share ideas and solutions, making this session a combination of Demonstration and Collaborative teaching (50% each). The focus throughout is on active learning to develop digital fluency.
Attendance Recorded: Yes

Teaching Method 3 - Independent Work with PG demonstrator back-up. Students continue their weekly tasks independently, with access by email to a demonstrator for help if they get stuck. Demonstrator available 5 hours per week.

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours           10

10

10

 30
Timetable (if known)              
Private Study 120
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
Online test (no time limit): Matlab techniques and data interpretation 2. There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment (each  0    60       
Online test (no time limit): Matlab techniques and global Carbon. There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Sch  0    20       
Online test 1 (no time limit): Matlab techniques and data interpretation There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessm  0    20       

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