Statistics for Linguistics

lfial2260  2020-2021  Louvain-la-Neuve

Statistics for Linguistics
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
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 tool -- introduction:
  • Quantitative analysis of linguistic data: descriptive and inferential statistics; introduction to regression analysis;
  • Data visualization.
Aims

At the end of this learning unit, the student is able to :

1 At the end of the course, students will be able to select and use appropriate quantitative methods to analyze linguistic phenomena with the help of a statistical software tool.
More practically, they will be able to use the statistical software tool R to explore linguistic data (descriptive statistics),represent data visually, and select the most appropriate statistics given the structure of their dataset
 
Content
The course will be organized in two main parts:
  1. 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).
  2. The second part of the course will be more practical in nature. It will give students the opportunity to practise through exercises.
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The teaching method will be a mix of traditional lectures and exercises
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The evaluation will be twofold:
  • Continuous assessment (40%): e.g. participation in class activities, tests and exercises
  • Written exam (60%)
In case of resit, the evaluation will be based on a written exam only (100%) 
Other information
This course requires a good command of English (receptive and productive skills).
Bibliography
  • Field, A. et Miles, J. and Field, Z. (2012). Discovering Statistics Using R. London : Sage Publications.
  • 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
Force majeure
Teaching methods
Online teaching (including exercise sessions) via Teams
Evaluation methods
The evaluation remains unchanged except for the fact that the written exam will be organized as a take-home exam.


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Linguistics