Data Literacy and Analysis

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Independently use the R environment, and know where to search for additional online resources.
• Contrast your empirical data with the theoretical assumptions to differentiate between the relative support for different conclusions.
• Present and interpret the results of statistical tests on given data sets.
• Compute statistical analyses in integrated workflows (reading data in, exporting report- and publication-quality figures) using the R environment.
• Identify statistical procedures appropriate to different types of hypotheses and data.

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.

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.

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.

Summative

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

Repeat Information

Repeat type: Internal & External