Statistical Programming in R

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Implementation of statistical procedures within the R environment

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Data visualisation - learning how to create high-quality figures, especially associated with more complex analyses (e.g. three dimensional scatter plots, Trellis displays, etc.).
• Data manipulation - acquiring skills in flexible matrix manipulation
• Scripting - programming an analysis in such a way that the script can be used with minimal effort for similar datasets and analyses and for especially large datasets

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• Understanding and implementing Linear Mixed Models (LMM)

This module is divided into two main components. The first component is Introduction into the R language and implementing Basic Statistical Methods. The second component is implementing the General Linear Model and Mixed Linear Models (MLM) in R.

A specific focus will be on scripting, data manipulation and advanced data visualisation. No prior knowledge concerning MLM or computer programming is required. An Introduction on the basic ideas of MLM will be conveyed as well as implementation of this technique for specific research questions.

Teaching and learning methods

Teaching Activities

Type: 10 weeks of 2 hours workshops + 2 additional 2 hour workshops in week 3 and week 6.

Hours: 24

Group Size: 25 maximum

Resources & Reading list

General Resources

Software requirements. R is open-source, free software which is available for download for the Windows, Mac OS X and Linux platform.

Textbooks

Alain Zuur, Elena Ieno, & Erik Meesters (2009). A Beginner's Guide To R. Springer.

Summative

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

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat Information

Repeat type: Internal & External