Birmingham Statistics for Linguists Summer School 2019

University of Birmingham
Monday 17 June (09:00) - Friday 21 June 2019 (17:00)

For more information and initial enquiries, contact the summer school convenor Dr Bodo Winter.


The University of Birmingham is organising its second “Statistics for Linguists” Summer School.

Over the course of five days, participants will learn how to process and analyse data using the R programming language. We will provide a comprehensive overview of current statistical methods that are commonly used in linguistics and related fields, with a focus on regression modelling and its extensions (generalized linear models, linear mixed effects models etc.). The ultimate goal is for participants to become competent users of these techniques and gain a better understanding of their own data.

The main sessions will cover topics such as:

  • Introduction to the R programming language
  • Data wrangling
  • Reproducible research practices
  • Data visualisation
  • Linear models
  • Poisson and logistic regression
  • Linear mixed effects models
  • Bayesian modelling
  • Simulating data for power and Type I error simulations 

Additional optional sessions (electives) will cover topics such as:

  • Generalised additive models
  • Resampling techniques (bootstrapping, permutation tests)
  • Classification and regression trees and random forests
  • Confirmatory and exploratory factor analysis
  • Path analysis and structural equation models
  • Multiple correspondence analysis
  • Cluster analysis
  • Corpus statistics

The summer school will be convened by Bodo Winter (University of Birmingham), Timo Roettger (Northwestern University) and Márton Sóskuthy (University of British Columbia).

Additional optional sessions will be offered by our local staff of quantitative linguists, including Isobelle Clarke, Dagmar Divjak, Matteo Fuoli, Jason Grafmiller, Jack Grieve, Michaela Mahlberg, Petar Milin and Viola Wiegand.

The workshop will combine theory sessions with hands-on analysis examples. There will be opportunities for students to present their own work and receive feedback from our expert team. We have planned social activities to also make this an opportunity for networking for all participants.

The summer school is open to undergraduate, postgraduate, and doctoral students, as well as researchers who want to improve their skills in applying statistical methods in their own research. No statistical, mathematical or programming background is required.

For more information and initial enquiries, contact the summer school convenor Dr Bodo Winter at