# Statistics for Linguistics

lclig2240  2017-2018  Louvain-la-Neuve

Statistics for Linguistics
10 credits
30.0 h + 15.0 h
Q2
Teacher(s)
François Thomas;
Language
French
Prerequisites
One course of introduction to linguistics.
Main themes
Data collection: descriptive and experimental methods, reliability and validity, sampling procedures.
Descriptive statistics: definitions, graphical representation, numerical summaries.
Using a statistical software
Inferential statistics : main concepts.
Basic statistical analyses and tests: frequency analysis (categorical data), testing hypotheses about means, correlation and regression, non parametric tests. Advanced statistical analyses and tests: interrater agreement measures, multivariate descriptive techniques, regression models for contingency tables, '.
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 use the main statistical tools and concepts of quantitative linguistics. He will be able to choose appropriate methods for specific research objectives and to use it in the framework of linguistic research. Most of all, the student will be able to make a critical review of the results obtained by a quantitative analysis. He will also be trained to use a statistical analysis 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 organization of the course is twofold :
1. The first part of the course consists in a theoretical approach in the field of textual data statistical analysis introducing the main concepts in statistics (descriptive statistics, inference, and modeling).
2. The second part of the course will provide a practical approach of the field. It will give the students the opportunity to practice what he/she has learned in the theoretical introduction through a personal research project covering real linguistic data.
Teaching methods
Lectures + readings + practical works
Evaluation methods
The evaluation is three-fold :
- continuous assessment (exercices during TP and readings) (20 %)
- written examination (30 %)
- personal written project (with an oral presentation) (50 %)
Other information
Support: slides; articles ou book chapters; i-campus (web site with forum and exercises).
Bibliography
Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
Howell, D. (2008). Méthodes statistiques en sciences humaines, Paris, De Boeck Université.
Muller, Charles (1992). Initiation aux méthodes de la statistique linguistique, Champion.
Rasinger, S.M. (2008). Quantitative Research in Linguistics. New York, Continuum International Publishing Group
Faculty or entity
LING

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

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in French and Romance Languages and Literatures : General
10

Master [120] in Linguistics
10

Master [120] in French and Romance Languages and Literatures : French as a Foreign Language
10

Master [120] in Modern Languages and Literatures : General
10

Master [120] in Ancient Languages and Literatures: Classics
10

Master [120] in Ancient and Modern Languages and Literatures
10

Master [120] in Ancient Languages and Literatures: Oriental Studies
10

Master [120] in Modern Languages and Literatures : German
10