Module ONS-1001:
Environmental data & analysis

Module Facts

Run by School of Ocean Sciences

20 Credits or 10 ECTS Credits

Semester 1 & 2

Organiser: Dr Martin Austin

Overall aims and purpose

To develop in students an understanding of the fundamental skills required by natural scientists to measure, map and quantify the environment in which they work. This includes the key concepts of the scientific method, experimental design, mapping, basic mathematical manipulations, statistical analysis and time series analysis.

Course content

This module concentrates on providing students with the basic skills for Natural Scientists, which focus on measuring, mapping and quantifying the environment. The course relies heavily on computer-based material and so the student also learns how to use and evaluate on-line information, as well as how to converse, discuss and learn via the Blackboard virtual learning environment.

The module begins by focusing on the scientific method, hypothesis setting and testing; these lead into the fundamental ideas concerning experimental design. Further topics include:

  • Introduction and description of distributions within scientific data
  • Ideas of probability
  • Unit systems, decimal places, orders of magnitude used in science
  • Mapping and spatial analysis techniques: maps, charts, contours, accuracy & precision.
  • Data analysis and manipulation using Excel
  • Time series analysis using Matlab
  • Graphing of linear systems
  • Coping with non-linearity in nature (logs etc.)
  • Examples of statistical tests: parametric versus non-parametric
  • Statistical tests using SPSS
  • Tests for difference: t-tests and ANOVA
  • Tests of association: regression and correlation

Assessment Criteria

threshold

A threshold student should have a basic knowledge of the scientific method, have a basic ability to quantitatively manipulate datasets using a range of fundamental mathematical tools, have a basic ability to apply and interpret spatial and temporal datasets and be able to use and interpret statistical tests.

good

A good student should competent at quantitatively manipulating datasets using a range of fundamental mathematical tools, have a good ability to apply and interpret spatial and temporal datasets and be able to confidently use and interpret statistical tests.

excellent

An excellent student should have a sophisticated knowledge of quantitatively manipulating datasets using a range of fundamental mathematical tools, have an advanced ability to apply and interpret spatial and temporal datasets and be highly skilled in the use and interpretation of statistical tests.

Learning outcomes

  1. Apply appropriate temporal analysis techniques to data and correctly interpret the outputs

  2. Show understanding of units of measure and dimensional analysis

  3. Have a sound grasp of basic numerical manipulation techniques

  4. Be able to use mathematical and graphical techniques to describe scientific phenomena

  5. Apply appropriate data analysis and statistical techniques to scientific data using Excel, Matlab and SPSS computer packages and correctly interpret the outcomes

  6. Have an awareness of how to plan and conduct a simple experiment with appropriate regard to design and analysis issues

  7. Apply appropriate spatial analysis techniques to data and correctly interpret the outputs

  8. Develop an understanding of the scientific method to develop ideas, make observations, and set and test hypotheses

  9. Be able to communicate the results of environmental scientific investigations to an appropriate audience

Assessment Methods

Type Name Description Weight
REPORT Fieldwork and data analysis scientific report 30
CLASS TEST T1 - Scientific method and hypothesis testing midterm 20
CLASS TEST T2 - Data analysis 1 - numeracy, Excel, distributions 30
CLASS TEST T3 - Time series analysis and Matlab skills OR Tests for difference 20

Teaching and Learning Strategy

Hours
Private study

Online information resources (1 information pack per week)

20
Workshop

Computer practicals

8
Lecture

Theory of mapping and measuring techniques

27
Individual Project

Supervised data analysis and write-up of subject-specific fieldwork exercise

10
Practical classes and workshops

Practical and laboratory exercises - mapping, surveying, sediments

13
Private study

(Approx. 6 hours per week.) Private self-study utilising the directed reading materials, and reinforcement of lecture, workshop and project materials.

114
Fieldwork

Fieldwork activity to collect appropriate data to map and measure the environment

8

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Safety-Consciousness - Having an awareness of your immediate environment, and confidence in adhering to health and safety regulations
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Resources

Pre- and Co-requisite Modules

Courses including this module

Compulsory in courses: