Data Literacy and Analysis

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 and hypothesis testing using marine examples drawn from the spectrum of activities routinely used in final year Honours projects.

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,
Student-led workshops to discuss experimental design in different circumstances.
Short videos of key definitions and concepts via Blackboard
Panopto lecture capture.

Study time
Type	Hours
Independent Study	80
Lecture	10
Practical classes and workshops	40
Tutorial	20
Total study time	150

Resources & Reading list

General Resources

Textbooks. • Getting Started with R (2017) Beckerman, Childs, Petchy. Oxford University Press • The New Statistics: An Introduction for Biologists (2015) Hector. Oxford University Press

Software. • Freely distributed R environment through the more intuitive RStudio interface, both of which are already part of the core University packages.

Assessment

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Computer-based workshop	100%

Repeat Information

Repeat type: Internal & External