Experimental Design and Data Analysis ENGLANG5092
- Academic Session: 2018-19
- School: School of Critical Studies
- Credits: 20
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: No
- Available to Erasmus Students: No
This course provides Masters' level students with a grounding in the most common quantitative, computational, and statistical methods that are used to analyse linguistic data. We will cover experimental design, probability, descriptive and inferential statistics, and computational methods for cleaning, visualising, and analysing data.
10 x 1hr lectures, 10 x 1hr practical workshops over 10 weeks as scheduled on MyCampus.
This course may be taught in conjunction with ENGLANG4063, as scheduled on MyCampus
This is one of the MSc options in English Language and Linguistics, and is an obligatory course for the MSc in Speech, Language and Sociolinguistics. The options that are running this session are available on MyCampus.
Requirements of Entry
Standard entry to postgraduate Masters at College Level.
ENGLANG5070: Modern English Language
Two technical exercises (one on data visualization and one on statistical analysis) - 25% each
One written assignment (plan of statistical analysis for an independent research project) 2500 words - 50 %
This course will provide the opportunity to:
■ Become familiar with the free, open-source software package R for data analysis and visualisation
■ Acquire a core understanding of probability and inferential statistics
■ Carry out a variety of statistical tests on different types of data
■ Analyse independently-collected data to answer a research question
■ Learn the common pitfalls and misconceptions in carrying out inferential statistical analyses
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ Clean and manipulate raw data sets so they are ready for analysis
■ Generate data visualisation to illustrate key patterns in linguistic data
■ Determine and carry out the appropriate statistical test for a variety of experimental questions about different data sets
■ Interpret the result of inferential statistics tests
■ Draw conclusions about whether research hypotheses have been supported by empirical data.
■ Plan the statistical analysis of an independent research project
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.