Statistical Programming in R

Learning Outcomes

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• 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
• 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

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)

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Implementation of statistical procedures within the R environment

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 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

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.