Birmingham Statistics for Linguists Summer School

The University of Birmingham is organising its first “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.

The summer school will be convened by Bodo Winter (University of Birmingham), Timo Roettger (Northwestern University) and Márton Sóskuthy (University of York). Additional optional sessions will be offered by our local staff of quantitative linguists, including Isobelle Clark, Matteo Fuoli, Jason Grafmiller, Jack Grieve, Michaela Mahlberg and Viola Wiegand.

We will provide a comprehensive overview of current statistical methods that are commonly used in linguistics and related fields. The ultimate goal is for participants to become competent users of these techniques and gain a better understanding of their own data.

The 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
• Growth Curve Analysis
• Generalised additive models

Additional optional sessions will cover topics such as:

• Mapping and Spatial Analysis
• Resampling techniques (bootstrapping, permutation tests)
• Multidimensional Scaling and Principal Components Analysis
• Classification and Regression Trees and Random Forests
• Confirmatory and Exploratory Factor Analysis
• Path Analysis and Structural Equation Models
• Multiple Correspondence Analysis
• Simulating data for power and Type I error simulations
• Corpus statistics and co-occurrence comparisons

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. Additional review materials will be available online after the course, including video recordings of each session.

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.