10 credits
22.5 h
Q1
Teacher(s)
Paquot Magali;
Language
English
Prerequisites
One course of introduction to linguistics.
Main themes
Data management in a statistical software : vectors, matrices, data frames, etc.
- quantitative analysis of linguistic data: classical univariate, bivariate and multivariate techniques; descriptive and inferential statistics; contemporary methods of analysis of language variation and change (distinctive collexeme analysis, SemanticVector Spaces, motion charts)
- data visualization in a statistical software
Aims
At the end of this learning unit, the student is able to : | |
| 1 | At the end of the course, the student will be able to select and use appropriate quantitative methods to analyze linguistic phenomena with the help of a statistical software . More practically, he will be able to use and understand the software provided in the course and adjust it for the purposes of his own research. He will also be able to represent his data visually with the help of the software. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
The course will be organized in two main parts:
- The first part of the course will provide a theoretical overview of statistics for linguistics and introduce the main concepts in statistics (descriptive statistics, inferencing, and modeling).
- The second part of the course will be more practical in nature. It will give students the opportunity to practise through exercises and a personal research project for which they will analyze real linguistic data.
Teaching methods
The teaching method will be a mix of traditional lectures and flipped classroom
Evaluation methods
The evaluation will be threefold:
- Continuous assessment (30%): participation in class activities, tests and exercises
- Written exam (30%)
- Research project (40%): individual research paper (or group research project that aims to analyze linguistic data for publication)
Other information
This course requires a good command of English (receptive and productive skills).
Online resources
https://moodleucl.uclouvain.be/course/view.php?id=12097
Bibliography
- Gries, St. Th. 2013. Statistics for Linguistics with R. A Practical Introduction. 2nd edition. Berlin: De Gruyter Mouton.
- R codes
- Slides and additional chapters available on Moodle
Gries, St. Th. 2013. Statistics for Linguistics with R. A Practical Introduction. 2nd edition. Berlin: De Gruyter Mouton.
Howell, D. C. (2016). Fundamental statistics for the behavioral sciences. Nelson Education.
Teaching materials
- Gries, St. Th. 2013. Statistics for Linguistics with R. A Practical Introduction. 2nd edition. Berlin: De Gruyter Mouton.
- R codes
- Slides and additional chapters available on Moodle
Faculty or entity
FIAL
