Data Analysis Using R
| Code | School | Level | Credits | Semesters |
| ENGL4364 | English | 4 | N/A | April Full Year UK, Full Year UK, January Full Year UK |
- Code
- ENGL4364
- School
- English
- Level
- 4
- Credits
- N/A
- Semesters
- April Full Year UK, Full Year UK, January Full Year UK
Summary
As language researchers, there are always new and exciting elements of production and comprehension that capture our attention. The next stage is to carefully design a study to investigate a particular question. But once we have the data, we need to decide whether our question has been answered and figure out what else our data might tell us about language or language users. This requires careful data analysis, which in turn depends on properly preparing our data (‘data wrangling’) and understanding which analyses to apply to our particular data. The goal of this pod is to equip students with the skills to carry out and interpret rigorous analyses that are appropriate to their data, using clear and reproducible code.
Target Students
Students registered on the School of English online masters scheme.
Assessment
- 100% Participation: Student Participation
Assessed by end of designated period
Educational Aims
This module comprises an optional component in the following pathways: Applied English, Applied Linguistics, and Applied Linguistics and ELT. It also forms a compulsory component in the Psycholinguistics pathway. As such, it contributes in its specific aims to the programme-level coverage of these pathways.Learning Outcomes
Demonstrate knowledge of key concepts and processes in data wrangling and data analysis.
Critically evaluate the elements of data wrangling and analysis that are suited to different types of data and research aims.
Apply knowledge of statistical analysis to appropriately interrogate data from original research.
Demonstrate knowledge and skills acquired to the appropriate disciplinary and professional standard.
Assimilate and present subject-specific material in an appropriate format (assessed within the ‘Assessment Portfolio’ 1, 2 or 3).