SOES2036 Quantitative Methods in Marine Science
Module Overview
This module develops analytical skills required for evidence-based interpretation of data generated in the Marine Sciences. The material will focus initially on both the philosophical background of statistical analysis, illustrating how applications in public documents often abuse the basic principles of graphical and statistical analysis. The module will then develop skills in computer literacy, graphical presentation and hypothesis testing using marine examples drawn from the spectrum of activities routinely used in final year Honours projects.
Aims and Objectives
Module Aims
To appreciate how the fundamental relationships of experimental design apply to all statistical analyses, not just formal experiments. To develop analytical skills to a level sufficient to understand the principles of marine data collection and the statistical modelling thereof To introduce and use the R environment for statistical analysis, graphical figure generation, result presentation and conclusion evaluation.
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Identify statistical procedures appropriate to different types of hypotheses and data.
- Independently use freely available software, and know where to search for additional online resources.
- Compute statistical analyses and generate publication-quality figures using the R environment.
- Present and interpret the results of statistical tests on given data sets
- Contrast your empirical data with the theoretical assumptions to differentiate between the relative support for different conclusions.
Syllabus
This module develops analytical skills required for evidence-based interpretation of data generated in the Marine Sciences. The material will focus initially on both the philosophical background of statistical analysis, illustrating how applications in public documents often abuse the basic principles of graphical and statistical analysis. The module will then develop skills in computer literacy, graphical presentation and hypothesis testing using marine examples drawn from the spectrum of activities routinely used in final year Honours projects.
Special Features
Reduces the number of hand-marked assessments by using MCQ. Makes better use of modern lecture capture methods, both Panopto recordings of lectures but also pre-recorded snippets of key definitions that do not change and so do not need updating year-on-year. Provides more one-on-one time between educators and students, through large group revision tutorials (trialled on BIOL6052 where students can anonymously submit requests for lecturers to revise old material) and more time for one-on-one practical classes. Keystone in the proposed quantitative stream on MB/OC pathways Builds on: Lectures & prac’s (SOES1001 Func Mar Biol) Lectures & prac’s (SOES1010 Quant Earth Ocean Sci) Should integrate with later analytical needs on (e.g., Falmouth field course, project requirements) through contact time in later modules.
Learning and Teaching
Teaching and learning methods
The overarching goal is to provide more one-on-one time between educators and students to overcome the initial steep learning curve presenting by statistics and statistical software. • Traditional lectures • Large-group tutorials led by educator based on anonymized student requests for material to revise. • Student-led practical sessions giving hands-on experience of the R environment, • Studenet-led workshops to discuss experimental design in different circumstances. • Short videos of key definitions and concepts via Blackboard • Panopto lecture capture.
Type | Hours |
---|---|
Practical classes and workshops | 18 |
Independent Study | 110 |
Lecture | 16 |
Tutorial | 6 |
Total study time | 150 |
Resources & Reading list
Software. Freely distributed R environment through the more intuitive RStudio interface, both of which are already part of the core University packages.
Lectures. All lectures and revision tutorials recorded using Panopto. Use flipped material to augment lectures – film brief videos of definition material that do not require updating each year.
Textbooks. New issue of Getting Started with R, which has a jellyfish on the front. John Fox’s Guide to Applied Regression.
Assessment
Formative
Class practicals
Summative
Method | Percentage contribution |
---|---|
MCQ-applied knowledge assessment | 70% |
MCQ-applied knowledge assessment | 30% |