Statistics for Linguistics

lfial2260  2021-2022  Louvain-la-Neuve

Statistics for Linguistics
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10 credits
22.5 h
Q1
Language
English
Prerequisites
One course of introduction to linguistics.
Main themes
Quantitative analysis of linguistic data with R
  • Data visualization
  • Descriptive statistics : definitions ; computing and representation
  • Inferential statistics: main concepts
  • Basic statistical analyses : frequency comparisons, means comparisons, non-parametric testing, correlationsques, correlations
  • (Theoretical) introduction to regression modelling and classification trees
Aims

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

At the end of the course, students will be able to select and use basic 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 (among basic approaches) given the structure of their dataset
They will also be able to understand a scientific article based on more sophisticated statistical techniques (e.g. regression modelling), and to critically examine the results of a quantitative study.
 
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
The teaching method will be a mix of traditional lectures and exercises
Evaluation methods
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


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

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