WARSZTATY
Multifactorial feature analysis.
A quantitative method for qualitative linguistics
19-21 listopada, IFP, UWr.
Prowadzi: prof. Dylan Glynn
dglynn@univ-paris8.fr
www.dsglynn. univ-paris8.fr
Program:
Multifactorial feature analysis.
A quantitative method for qualitative linguistics
Dylan Glynn
This short practical course will introduce multifactorial usage-feature analysis (also called the
profile-based approach). This is a corpus-based method that can be applied to research
questions typical of Cognitive and Functional Linguistics. It is currently extremely popular in
the fields of semantics / pragmatics, conceptual / functional analysis, or variationist /
sociolinguistic research and morpho-syntax and construction grammar. Essentially, the
method can be applied to any phenomenon in language and culture that is motivated.
There are two parts to this methodology. The first is the usage-feature analysis and the second
is the multivariate statistics that are needed to interpret the results of the feature analysis.
Linguists are always concerned that the statistics will be difficult. This is not the case at all.
The statistics are merely a tool to enable us to improve the research we already do. The
linguistics research questions that you all work on remain difficult. The statistics will allow
you to identify things would not otherwise see and to make falsifiable claims in ways that you
otherwise could not, but the linguistics remain the point and the most difficult part of research.
Before we start, I will put on line materials for you. I will also ask you to send me a 1-2 line
summary of your research interests to help me better orientate the content of the course. The
course will be broken down into 6 sessions of two hours, which will be held over the course
of 3 days. Over the course of the workshop I will also discuss how these methods are
applicable to your own work. After the workshop, I will be able to help you apply these
techniques in your own projects.
Requirements
No prior knowledge of statistics is needed. A computer with internet access is needed.
Aims
To understand and apply multifactorial usage-feature analysis. To run the basic functionalities
of R, the statistical programming environment. To be able to apply and interpret basic tests
for statistical significance, and run multivariate statistical analyses on complex data. To be
able to apply and interpret binary logistic regression modeling of complex categorical data.
Session 1. Introduction
A summary of the method, it’s strengths and weakness and possible applications.
In this session you sit and listen.
Session 2. Research Question
Choice of research topic, collection of data, and development of a coding schema.
In this session we work together to obtain data to learn the method.
Session 3. R
The statistical program for doing statistics.
In this session we introduce the program R and learn how to load data and to run some basic
tests
Session 4. Correspondence analysis
A multivariate statistical technique for identifying complex patterns of association in the data
In this session we learn how to apply and interpret the technique
Session 5. Cluster Analysis
A multivariate statistical technique for identifying groups of similarities in the data
In this session we learn how to apply and interpret the technique
Session 6. Logistic Regression
Confirmatory modeling of data and calculation of predictive accuracy.
In this session we learn how to apply and interpret the technique
Terminy:
wtorek 10.00 - 15.00 s. 121
środa 18.00 - 20:30 s. Mikulskiego (wcześniej, około godziny 16.00, planujemy herbatę w
kawiarni, która ma wi-fi, aby można było ściągnąć z sieci odpowiednie programy przydatne
w dalszej części zajęć)
czwartek 11.00 - 13.00 s. 121.
Zgłoszenia i zapisy (w miarę wolnych miejsc!):
dr hab. Agnieszka Libura, IFP: agnieszka.libura@uni.wroc.pl